ICLR 2025
3703 papers
$\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun $\sigma$-Zero: Gradient-Based Optimization of $\ell_0$-Norm Adversarial Examples
Antonio Emanuele Cinà, Francesco Villani, Maura Pintor, Lea Schönherr, Battista Biggio, Marcello Pelillo $\text{D}_{2}\text{O}$: Dynamic Discriminative Operations for Efficient Long-Context Inference of Large Language Models
Zhongwei Wan, Xinjian Wu, Yu Zhang, Yi Xin, Chaofan Tao, Zhihong Zhu, Xin Wang, Siqi Luo, Jing Xiong, Longyue Wang, Mi Zhang $InterLCM$: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration
Senmao Li, Kai Wang, Joost van de Weijer, Fahad Shahbaz Khan, Chun-Le Guo, Shiqi Yang, Yaxing Wang, Jian Yang, Ming-Ming Cheng $q$-Exponential Family for Policy Optimization
Lingwei Zhu, Haseeb Shah, Han Wang, Yukie Nagai, Martha White 3D Vision-Language Gaussian Splatting
Qucheng Peng, Benjamin Planche, Zhongpai Gao, Meng Zheng, Anwesa Choudhuri, Terrence Chen, Chen Chen, Ziyan Wu 3D-Properties: Identifying Challenges in DPO and Charting a Path Forward
Yuzi Yan, Yibo Miao, Jialian Li, YipinZhang, Jian Xie, Zhijie Deng, Dong Yan 3D-Spatial Multimodal Memory
Xueyan Zou, Yuchen Song, Ri-Zhao Qiu, Xuanbin Peng, Jianglong Ye, Sifei Liu, Xiaolong Wang 3DitScene: Editing Any Scene via Language-Guided Disentangled Gaussian Splatting
Qihang Zhang, Yinghao Xu, Chaoyang Wang, Hsin-Ying Lee, Gordon Wetzstein, Bolei Zhou, Ceyuan Yang 3DTrajMaster: Mastering 3D Trajectory for Multi-Entity Motion in Video Generation
Xiao Fu, Xian Liu, Xintao Wang, Sida Peng, Menghan Xia, Xiaoyu Shi, Ziyang Yuan, Pengfei Wan, Di Zhang, Dahua Lin 4K4DGen: Panoramic 4D Generation at 4k Resolution
Renjie Li, Panwang Pan, Bangbang Yang, Dejia Xu, Shijie Zhou, Xuanyang Zhang, Zeming Li, Achuta Kadambi, Zhangyang Wang, Zhengzhong Tu, Zhiwen Fan 6d Object Pose Tracking in Internet Videos for Robotic Manipulation
Georgy Ponimatkin, Martin Cífka, Tomas Soucek, Médéric Fourmy, Yann Labbé, Vladimir Petrik, Josef Sivic 6DGS: Enhanced Direction-Aware Gaussian Splatting for Volumetric Rendering
Zhongpai Gao, Benjamin Planche, Meng Zheng, Anwesa Choudhuri, Terrence Chen, Ziyan Wu A Benchmark for Semantic Sensitive Information in LLMs Outputs
Qingjie Zhang, Han Qiu, Di Wang, Yiming Li, Tianwei Zhang, Wenyu Zhu, Haiqin Weng, Liu Yan, Chao Zhang A Closer Look at Machine Unlearning for Large Language Models
Xiaojian Yuan, Tianyu Pang, Chao Du, Kejiang Chen, Weiming Zhang, Min Lin A Coefficient Makes SVRG Effective
Yida Yin, Zhiqiu Xu, Zhiyuan Li, Trevor Darrell, Zhuang Liu A Formal Framework for Understanding Length Generalization in Transformers
Xinting Huang, Andy Yang, Satwik Bhattamishra, Yash Sarrof, Andreas Krebs, Hattie Zhou, Preetum Nakkiran, Michael Hahn A Generalist Hanabi Agent
Arjun V Sudhakar, Hadi Nekoei, Mathieu Reymond, Miao Liu, Janarthanan Rajendran, Sarath Chandar A Generic Framework for Conformal Fairness
Aditya T. Vadlamani, Anutam Srinivasan, Pranav Maneriker, Ali Payani, Srinivasan Parthasarathy A Geometric Framework for Understanding Memorization in Generative Models
Brendan Leigh Ross, Hamidreza Kamkari, Tongzi Wu, Rasa Hosseinzadeh, Zhaoyan Liu, George Stein, Jesse C. Cresswell, Gabriel Loaiza-Ganem A Graph Enhanced Symbolic Discovery Framework for Efficient Logic Optimization
Yinqi Bai, Jie Wang, Lei Chen, Zhihai Wang, Yufei Kuang, Mingxuan Yuan, Jianye Hao, Feng Wu A Large-Scale Training Paradigm for Graph Generative Models
Yu Wang, Ryan A. Rossi, Namyong Park, Huiyuan Chen, Nesreen K. Ahmed, Puja Trivedi, Franck Dernoncourt, Danai Koutra, Tyler Derr A Meta-Learning Approach to Bayesian Causal Discovery
Anish Dhir, Matthew Ashman, James Requeima, Mark van der Wilk A Multi-Power Law for Loss Curve Prediction Across Learning Rate Schedules
Kairong Luo, Haodong Wen, Shengding Hu, Zhenbo Sun, Zhiyuan Liu, Maosong Sun, Kaifeng Lyu, Wenguang Chen A New Perspective on Shampoo's Preconditioner
Depen Morwani, Itai Shapira, Nikhil Vyas, Eran Malach, Sham M. Kakade, Lucas Janson A Periodic Bayesian Flow for Material Generation
Hanlin Wu, Yuxuan Song, Jingjing Gong, Ziyao Cao, Yawen Ouyang, Jianbing Zhang, Hao Zhou, Wei-Ying Ma, Jingjing Liu A Riemannian Framework for Learning Reduced-Order Lagrangian Dynamics
Katharina Friedl, Noémie Jaquier, Jens Lundell, Tamim Asfour, Danica Kragic A Robust Method to Discover Causal or Anticausal Relation
Yu Yao, Yang Zhou, Bo Han, Mingming Gong, Kun Zhang, Tongliang Liu A Sanity Check for AI-Generated Image Detection
Shilin Yan, Ouxiang Li, Jiayin Cai, Yanbin Hao, Xiaolong Jiang, Yao Hu, Weidi Xie A Second-Order Perspective on Model Compositionality and Incremental Learning
Angelo Porrello, Lorenzo Bonicelli, Pietro Buzzega, Monica Millunzi, Simone Calderara, Rita Cucchiara A Simple Approach to Unifying Diffusion-Based Conditional Generation
Xirui Li, Charles Herrmann, Kelvin C.K. Chan, Yinxiao Li, Deqing Sun, Chao Ma, Ming-Hsuan Yang A Simple Framework for Open-Vocabulary Zero-Shot Segmentation
Thomas Stegmüller, Tim Lebailly, Nikola Đukić, Behzad Bozorgtabar, Tinne Tuytelaars, Jean-Philippe Thiran A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yian Ma, Biwei Huang A Statistical Framework for Ranking LLM-Based Chatbots
Siavash Ameli, Siyuan Zhuang, Ion Stoica, Michael W. Mahoney A Stochastic Approach to the Subset Selection Problem via Mirror Descent
Dan Greenstein, Elazar Gershuni, Ilan Ben-Bassat, Yaroslav Fyodorov, Ran Moshe, Fiana Raiber, Alex Shtoff, Oren Somekh, Nadav Hallak A Theory of Initialisation's Impact on Specialisation
Devon Jarvis, Sebastian Lee, Clémentine Carla Juliette Dominé, Andrew M Saxe, Stefano Sarao Mannelli A Training-Free Sub-Quadratic Cost Transformer Model Serving Framework with Hierarchically Pruned Attention
Heejun Lee, Geon Park, Youngwan Lee, Jaduk Suh, Jina Kim, Wonyong Jeong, Bumsik Kim, Hyemin Lee, Myeongjae Jeon, Sung Ju Hwang A Transfer Attack to Image Watermarks
Yuepeng Hu, Zhengyuan Jiang, Moyang Guo, Neil Zhenqiang Gong A Transfer Learning Framework for Weak to Strong Generalization
Seamus Somerstep, Felipe Maia Polo, Moulinath Banerjee, Yaacov Ritov, Mikhail Yurochkin, Yuekai Sun A Truncated Newton Method for Optimal Transport
Mete Kemertas, Amir-massoud Farahmand, Allan Douglas Jepson A Watermark for Order-Agnostic Language Models
Ruibo Chen, Yihan Wu, Yanshuo Chen, Chenxi Liu, Junfeng Guo, Heng Huang A-Bench: Are LMMs Masters at Evaluating AI-Generated Images?
Zicheng Zhang, Haoning Wu, Chunyi Li, Yingjie Zhou, Wei Sun, Xiongkuo Min, Zijian Chen, Xiaohong Liu, Weisi Lin, Guangtao Zhai A3D: Does Diffusion Dream About 3D Alignment?
Savva Victorovich Ignatyev, Nina Konovalova, Daniil Selikhanovych, Oleg Voynov, Nikolay Patakin, Ilya Olkov, Dmitry Senushkin, Alexey Artemov, Anton Konushin, Alexander Filippov, Peter Wonka, Evgeny Burnaev Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research
Michał Bortkiewicz, Władysław Pałucki, Vivek Myers, Tadeusz Dziarmaga, Tomasz Arczewski, Łukasz Kuciński, Benjamin Eysenbach Accelerating Inference of Retrieval-Augmented Generation via Sparse Context Selection
Yun Zhu, Jia-Chen Gu, Caitlin Sikora, Ho Ko, Yinxiao Liu, Chu-Cheng Lin, Lei Shu, Liangchen Luo, Lei Meng, Bang Liu, Jindong Chen Accelerating Neural Network Training: An Analysis of the AlgoPerf Competition
Priya Kasimbeg, Frank Schneider, Runa Eschenhagen, Juhan Bae, Chandramouli Shama Sastry, Mark Saroufim, Boyuan Feng, Less Wright, Edward Z. Yang, Zachary Nado, Sourabh Medapati, Philipp Hennig, Michael Rabbat, George E. Dahl Accelerating Neural ODEs: A Variational Formulation-Based Approach
Hongjue Zhao, Yuchen Wang, Hairong Qi, Zijie Huang, Han Zhao, Lui Sha, Huajie Shao Accelerating Training with Neuron Interaction and Nowcasting Networks
Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie, Eugene Belilovsky, Simon Lacoste-Julien ACE: All-Round Creator and Editor Following Instructions via Diffusion Transformer
Zhen Han, Zeyinzi Jiang, Yulin Pan, Jingfeng Zhang, Chaojie Mao, Chen-Wei Xie, Yu Liu, Jingren Zhou ACES: Automatic Cohort Extraction System for Event-Stream Datasets
Justin Xu, Jack Gallifant, Alistair Johnson, Matthew B.A. McDermott Action Abstractions for Amortized Sampling
Oussama Boussif, Lena Nehale Ezzine, Joseph D Viviano, Michał Koziarski, Moksh Jain, Nikolay Malkin, Emmanuel Bengio, Rim Assouel, Yoshua Bengio Active Learning for Neural PDE Solvers
Daniel Musekamp, Marimuthu Kalimuthu, David Holzmüller, Makoto Takamoto, Mathias Niepert Active Task Disambiguation with LLMs
Kasia Kobalczyk, Nicolás Astorga, Tennison Liu, Mihaela van der Schaar ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning
Yarden As, Bhavya Sukhija, Lenart Treven, Carmelo Sferrazza, Stelian Coros, Andreas Krause Ada-K Routing: Boosting the Efficiency of MoE-Based LLMs
Tongtian Yue, Longteng Guo, Jie Cheng, Xuange Gao, Hua Huang, Jing Liu AdaFisher: Adaptive Second Order Optimization via Fisher Information
Damien MARTINS Gomes, Yanlei Zhang, Eugene Belilovsky, Guy Wolf, Mahdi S. Hosseini AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation
Yuning Cui, Syed Waqas Zamir, Salman Khan, Alois Knoll, Mubarak Shah, Fahad Shahbaz Khan Adam-Mini: Use Fewer Learning Rates to Gain More
Yushun Zhang, Congliang Chen, Ziniu Li, Tian Ding, Chenwei Wu, Diederik P Kingma, Yinyu Ye, Zhi-Quan Luo, Ruoyu Sun AdaManip: Adaptive Articulated Object Manipulation Environments and Policy Learning
Yuanfei Wang, Xiaojie Zhang, Ruihai Wu, Yu Li, Yan Shen, Mingdong Wu, Zhaofeng He, Yizhou Wang, Hao Dong Adapters for Altering LLM Vocabularies: What Languages Benefit the Most?
HyoJung Han, Akiko Eriguchi, Haoran Xu, Hieu Hoang, Marine Carpuat, Huda Khayrallah Adaptive Backtracking Line Search
Joao V. Cavalcanti, Laurent Lessard, Ashia C. Wilson Adaptive Camera Sensor for Vision Models
Eunsu Baek, Sung-hwan Han, Taesik Gong, Hyung-Sin Kim Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats
Jiaxin Wen, Vivek Hebbar, Caleb Larson, Aryan Bhatt, Ansh Radhakrishnan, Mrinank Sharma, Henry Sleight, Shi Feng, He He, Ethan Perez, Buck Shlegeris, Akbir Khan Adaptive Energy Alignment for Accelerating Test-Time Adaptation
Wonjeong Choi, Do-Yeon Kim, Jungwuk Park, Jungmoon Lee, Younghyun Park, Dong-Jun Han, Jaekyun Moon Adaptive Gradient Clipping for Robust Federated Learning
Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Ahmed Jellouli, Geovani Rizk, John Stephan Adaptive Length Image Tokenization via Recurrent Allocation
Shivam Duggal, Phillip Isola, Antonio Torralba, William T. Freeman Adaptive Methods Through the Lens of SDEs: Theoretical Insights on the Role of Noise
Enea Monzio Compagnoni, Tianlin Liu, Rustem Islamov, Frank Norbert Proske, Antonio Orvieto, Aurelien Lucchi Adaptive Teachers for Amortized Samplers
Minsu Kim, Sanghyeok Choi, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio AdaWM: Adaptive World Model Based Planning for Autonomous Driving
Hang Wang, Xin Ye, Feng Tao, Chenbin Pan, Abhirup Mallik, Burhaneddin Yaman, Liu Ren, Junshan Zhang ADBM: Adversarial Diffusion Bridge Model for Reliable Adversarial Purification
Xiao Li, Wenxuan Sun, Huanran Chen, Qiongxiu Li, Yingzhe He, Jie Shi, Xiaolin Hu Adding Conditional Control to Diffusion Models with Reinforcement Learning
Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Sunyuan Kung, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali Addressing Label Shift in Distributed Learning via Entropy Regularization
Zhiyuan Wu, Changkyu Choi, Xiangcheng Cao, Volkan Cevher, Ali Ramezani-Kebrya Advancing LLM Reasoning Generalists with Preference Trees
Lifan Yuan, Ganqu Cui, Hanbin Wang, Ning Ding, Xingyao Wang, Boji Shan, Zeyuan Liu, Jia Deng, Huimin Chen, Ruobing Xie, Yankai Lin, Zhenghao Liu, Bowen Zhou, Hao Peng, Zhiyuan Liu, Maosong Sun Advancing Out-of-Distribution Detection via Local Neuroplasticity
Alessandro Canevaro, Julian Schmidt, Mohammad Sajad Marvi, Hang Yu, Georg Martius, Julian Jordan Advantage Alignment Algorithms
Juan Agustin Duque, Milad Aghajohari, Tim Cooijmans, Razvan Ciuca, Tianyu Zhang, Gauthier Gidel, Aaron Courville Adversarial Attacks on Data Attribution
Xinhe Wang, Pingbang Hu, Junwei Deng, Jiaqi W. Ma Adversarial Machine Unlearning
Zonglin Di, Sixie Yu, Yevgeniy Vorobeychik, Yang Liu Adversarial Mixup Unlearning
Zhuoyi Peng, Yixuan Tang, Yi Yang Adversarially Robust Anomaly Detection Through Spurious Negative Pair Mitigation
Hossein Mirzaei, Mojtaba Nafez, Jafar Habibi, Mohammad Sabokrou, Mohammad Hossein Rohban AFlow: Automating Agentic Workflow Generation
Jiayi Zhang, Jinyu Xiang, Zhaoyang Yu, Fengwei Teng, Xiong-Hui Chen, Jiaqi Chen, Mingchen Zhuge, Xin Cheng, Sirui Hong, Jinlin Wang, Bingnan Zheng, Bang Liu, Yuyu Luo, Chenglin Wu Agent S: An Open Agentic Framework That Uses Computers like a Human
Saaket Agashe, Jiuzhou Han, Shuyu Gan, Jiachen Yang, Ang Li, Xin Eric Wang Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-Based Agents
Hanrong Zhang, Jingyuan Huang, Kai Mei, Yifei Yao, Zhenting Wang, Chenlu Zhan, Hongwei Wang, Yongfeng Zhang Agent-Oriented Planning in Multi-Agent Systems
Ao Li, Yuexiang Xie, Songze Li, Fugee Tsung, Bolin Ding, Yaliang Li AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents
Maksym Andriushchenko, Alexandra Souly, Mateusz Dziemian, Derek Duenas, Maxwell Lin, Justin Wang, Dan Hendrycks, Andy Zou, J Zico Kolter, Matt Fredrikson, Yarin Gal, Xander Davies AgentOccam: A Simple yet Strong Baseline for LLM-Based Web Agents
Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis, Huzefa Rangwala AgentRefine: Enhancing Agent Generalization Through Refinement Tuning
Dayuan Fu, Keqing He, Yejie Wang, Wentao Hong, Zhuoma GongQue, Weihao Zeng, Wei Wang, Jingang Wang, Xunliang Cai, Weiran Xu Agents' Room: Narrative Generation Through Multi-Step Collaboration
Fantine Huot, Reinald Kim Amplayo, Jennimaria Palomaki, Alice Shoshana Jakobovits, Elizabeth Clark, Mirella Lapata AgentSquare: Automatic LLM Agent Search in Modular Design Space
Yu Shang, Yu Li, Keyu Zhao, Likai Ma, Jiahe Liu, Fengli Xu, Yong Li AgentStudio: A Toolkit for Building General Virtual Agents
Longtao Zheng, Zhiyuan Huang, Zhenghai Xue, Xinrun Wang, Bo An, Shuicheng Yan AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorials
Yiheng Xu, Dunjie Lu, Zhennan Shen, Junli Wang, Zekun Wang, Yuchen Mao, Caiming Xiong, Tao Yu AHA: A Vision-Language-Model for Detecting and Reasoning over Failures in Robotic Manipulation
Jiafei Duan, Wilbert Pumacay, Nishanth Kumar, Yi Ru Wang, Shulin Tian, Wentao Yuan, Ranjay Krishna, Dieter Fox, Ajay Mandlekar, Yijie Guo AI as Humanity’s Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text Against Web Text
Ximing Lu, Melanie Sclar, Skyler Hallinan, Niloofar Mireshghallah, Jiacheng Liu, Seungju Han, Allyson Ettinger, Liwei Jiang, Khyathi Chandu, Nouha Dziri, Yejin Choi AI Sandbagging: Language Models Can Strategically Underperform on Evaluations
Teun van der Weij, Felix Hofstätter, Oliver Jaffe, Samuel F. Brown, Francis Rhys Ward AIMS.au: A Dataset for the Analysis of Modern Slavery Countermeasures in Corporate Statements
Adriana Eufrosina Bora, Pierre-Luc St-Charles, Mirko Bronzi, Arsene Fansi Tchango, Bruno Rousseau, Kerrie Mengersen Aioli: A Unified Optimization Framework for Language Model Data Mixing
Mayee F Chen, Michael Y. Hu, Nicholas Lourie, Kyunghyun Cho, Christopher Re Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems
Jindong Tian, Yuxuan Liang, Ronghui Xu, Peng Chen, Chenjuan Guo, Aoying Zhou, Lujia Pan, Zhongwen Rao, Bin Yang AIR-BENCH 2024: A Safety Benchmark Based on Regulation and Policies Specified Risk Categories
Yi Zeng, Yu Yang, Andy Zhou, Jeffrey Ziwei Tan, Yuheng Tu, Yifan Mai, Kevin Klyman, Minzhou Pan, Ruoxi Jia, Dawn Song, Percy Liang, Bo Li Aligned Better, Listen Better for Audio-Visual Large Language Models
Yuxin Guo, Shuailei Ma, Shijie Ma, Xiaoyi Bao, Chen-Wei Xie, Kecheng Zheng, Tingyu Weng, Siyang Sun, Yun Zheng, Wei Zou Aligned Datasets Improve Detection of Latent Diffusion-Generated Images
Anirudh Sundara Rajan, Utkarsh Ojha, Jedidiah Schloesser, Yong Jae Lee Aligned LLMs Are Not Aligned Browser Agents
Priyanshu Kumar, Elaine Lau, Saranya Vijayakumar, Tu Trinh, Elaine T Chang, Vaughn Robinson, Shuyan Zhou, Matt Fredrikson, Sean M. Hendryx, Summer Yue, Zifan Wang Aligning Human Motion Generation with Human Perceptions
Haoru Wang, Wentao Zhu, Luyi Miao, Yishu Xu, Feng Gao, Qi Tian, Yizhou Wang Aligning Language Models with Demonstrated Feedback
Omar Shaikh, Michelle S. Lam, Joey Hejna, Yijia Shao, Hyundong Justin Cho, Michael S. Bernstein, Diyi Yang Aligning Visual Contrastive Learning Models via Preference Optimization
Amirabbas Afzali, Borna Khodabandeh, Ali Rasekh, Mahyar JafariNodeh, Sepehr Kazemi Ranjbar, Simon Gottschalk ALLaM: Large Language Models for Arabic and English
M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, Nouf M. Alotaibi, Hisham Abdullah Alyahya, Sultan AlRashed, Faisal Abdulrahman Mirza, Shaykhah Z. Alsubaie, Hassan A. Alahmed, Ghadah Alabduljabbar, Raghad Alkhathran, Yousef Almushayqih, Raneem Alnajim, Salman Alsubaihi, Maryam Al Mansour, Saad Amin Hassan, Dr. Majed Alrubaian, Ali Alammari, Zaki Alawami, Abdulmohsen Al-Thubaity, Ahmed Abdelali, Jeril Kuriakose, Abdalghani Abujabal, Nora Al-Twairesh, Areeb Alowisheq, Haidar Khan AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models
Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Jie Shi, Xiang Wang, Xiangnan He, Tat-Seng Chua Amulet: ReAlignment During Test Time for Personalized Preference Adaptation of LLMs
Zhaowei Zhang, Fengshuo Bai, Qizhi Chen, Chengdong Ma, Mingzhi Wang, Haoran Sun, Zilong Zheng, Yaodong Yang An Asynchronous Bundle Method for Distributed Learning Problems
Daniel Cederberg, Xuyang Wu, Stephen P. Boyd, Mikael Johansson An Effective Theory of Bias Amplification
Arjun Subramonian, Samuel Bell, Levent Sagun, Elvis Dohmatob An Empirical Analysis of Uncertainty in Large Language Model Evaluations
Qiujie Xie, Qingqiu Li, Zhuohao Yu, Yuejie Zhang, Yue Zhang, Linyi Yang An Engorgio Prompt Makes Large Language Model Babble on
Jianshuo Dong, Ziyuan Zhang, Qingjie Zhang, Tianwei Zhang, Hao Wang, Hewu Li, Qi Li, Chao Zhang, Ke Xu, Han Qiu An Evolved Universal Transformer Memory
Edoardo Cetin, Qi Sun, Tianyu Zhao, Yujin Tang An Image Is Worth More than 16x16 Patches: Exploring Transformers on Individual Pixels
Duy Kien Nguyen, Mido Assran, Unnat Jain, Martin R. Oswald, Cees G. M. Snoek, Xinlei Chen An Information Criterion for Controlled Disentanglement of Multimodal Data
Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka, Tommi Jaakkola, Caroline Uhler Analytic DAG Constraints for Differentiable DAG Learning
Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents
Christopher Rawles, Sarah Clinckemaillie, Yifan Chang, Jonathan Waltz, Gabrielle Lau, Marybeth Fair, Alice Li, William E Bishop, Wei Li, Folawiyo Campbell-Ajala, Daniel Kenji Toyama, Robert James Berry, Divya Tyamagundlu, Timothy P Lillicrap, Oriana Riva Animate-X: Universal Character Image Animation with Enhanced Motion Representation
Shuai Tan, Biao Gong, Xiang Wang, Shiwei Zhang, DanDan Zheng, Ruobing Zheng, Kecheng Zheng, Jingdong Chen, Ming Yang Answer, Assemble, Ace: Understanding How LMs Answer Multiple Choice Questions
Sarah Wiegreffe, Oyvind Tafjord, Yonatan Belinkov, Hannaneh Hajishirzi, Ashish Sabharwal Anti-Exposure Bias in Diffusion Models
Junyu Zhang, Daochang Liu, Eunbyung Park, Shichao Zhang, Chang Xu Any-Step Dynamics Model Improves Future Predictions for Online and Offline Reinforcement Learning
Haoxin Lin, Yu-Yan Xu, Yihao Sun, Zhilong Zhang, Yi-Chen Li, Chengxing Jia, Junyin Ye, Jiaji Zhang, Yang Yu Anyprefer: An Agentic Framework for Preference Data Synthesis
Yiyang Zhou, Zhaoyang Wang, Tianle Wang, Shangyu Xing, Peng Xia, Bo Li, Kaiyuan Zheng, Zijian Zhang, Zhaorun Chen, Wenhao Zheng, Xuchao Zhang, Chetan Bansal, Weitong Zhang, Ying Wei, Mohit Bansal, Huaxiu Yao ARB-LLM: Alternating Refined Binarizations for Large Language Models
Zhiteng Li, Xianglong Yan, Tianao Zhang, Haotong Qin, Dong Xie, Jiang Tian, Zhongchao Shi, Linghe Kong, Yulun Zhang, Xiaokang Yang ARLON: Boosting Diffusion Transformers with Autoregressive Models for Long Video Generation
Zongyi Li, Shujie Hu, Shujie Liu, Long Zhou, Jeongsoo Choi, Lingwei Meng, Xun Guo, Jinyu Li, Hefei Ling, Furu Wei Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model
Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Yecheng Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton Artificial Kuramoto Oscillatory Neurons
Takeru Miyato, Sindy Löwe, Andreas Geiger, Max Welling ASTrA: Adversarial Self-Supervised Training with Adaptive-Attacks
Prakash Chandra Chhipa, Gautam Vashishtha, Settur Jithamanyu, Rajkumar Saini, Mubarak Shah, Marcus Liwicki AstroCompress: A Benchmark Dataset for Multi-Purpose Compression of Astronomical Data
Tuan Truong, Rithwik Sudharsan, Yibo Yang, Peter Xiangyuan Ma, Ruihan Yang, Stephan Mandt, Joshua S. Bloom Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models
Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux, Arian Hosseini, Rishabh Agarwal, Aaron Courville Atlas Gaussians Diffusion for 3D Generation
Haitao Yang, Yuan Dong, Hanwen Jiang, Dejia Xu, Georgios Pavlakos, Qixing Huang AtomSurf: Surface Representation for Learning on Protein Structures
Vincent Mallet, Yangyang Miao, Souhaib Attaiki, Bruno Correia, Maks Ovsjanikov Attention as a Hypernetwork
Simon Schug, Seijin Kobayashi, Yassir Akram, Joao Sacramento, Razvan Pascanu Attention Layers Provably Solve Single-Location Regression
Pierre Marion, Raphaël Berthier, Gérard Biau, Claire Boyer Attention with Markov: A Curious Case of Single-Layer Transformers
Ashok Vardhan Makkuva, Marco Bondaschi, Adway Girish, Alliot Nagle, Martin Jaggi, Hyeji Kim, Michael Gastpar Audio Large Language Models Can Be Descriptive Speech Quality Evaluators
Chen Chen, Yuchen Hu, Siyin Wang, Helin Wang, Zhehuai Chen, Chao Zhang, Chao-Han Huck Yang, EngSiong Chng AugKD: Ingenious Augmentations Empower Knowledge Distillation for Image Super-Resolution
Yun Zhang, Wei Li, Simiao Li, Hanting Chen, Zhijun Tu, Bingyi Jing, Shaohui Lin, Jie Hu, Wenjia Wang AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark
Wenhao Chai, Enxin Song, Yilun Du, Chenlin Meng, Vashisht Madhavan, Omer Bar-Tal, Jenq-Neng Hwang, Saining Xie, Christopher D Manning AutoBencher: Towards Declarative Benchmark Construction
Xiang Lisa Li, Farzaan Kaiyom, Evan Zheran Liu, Yifan Mai, Percy Liang, Tatsunori Hashimoto AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs
Xiaogeng Liu, Peiran Li, G. Edward Suh, Yevgeniy Vorobeychik, Zhuoqing Mao, Somesh Jha, Patrick McDaniel, Huan Sun, Bo Li, Chaowei Xiao AutoG: Towards Automatic Graph Construction from Tabular Data
Zhikai Chen, Han Xie, Jian Zhang, Xiang Song, Jiliang Tang, Huzefa Rangwala, George Karypis Automated Filtering of Human Feedback Data for Aligning Text-to-Image Diffusion Models
Yongjin Yang, Sihyeon Kim, Hojung Jung, Sangmin Bae, SangMook Kim, Se-Young Yun, Kimin Lee Automated Proof Generation for Rust Code via Self-Evolution
Tianyu Chen, Shuai Lu, Shan Lu, Yeyun Gong, Chenyuan Yang, Xuheng Li, Md Rakib Hossain Misu, Hao Yu, Nan Duan, Peng Cheng, Fan Yang, Shuvendu K Lahiri, Tao Xie, Lidong Zhou Automatic Curriculum Expert Iteration for Reliable LLM Reasoning
Zirui Zhao, Hanze Dong, Amrita Saha, Caiming Xiong, Doyen Sahoo Autonomous Evaluation of LLMs for Truth Maintenance and Reasoning Tasks
Rushang Karia, Daniel Richard Bramblett, Daksh Dobhal, Siddharth Srivastava Autoregressive Pretraining with Mamba in Vision
Sucheng Ren, Xianhang Li, Haoqin Tu, Feng Wang, Fangxun Shu, Lei Zhang, Jieru Mei, Linjie Yang, Peng Wang, Heng Wang, Alan Yuille, Cihang Xie Autoregressive Video Generation Without Vector Quantization
Haoge Deng, Ting Pan, Haiwen Diao, Zhengxiong Luo, Yufeng Cui, Huchuan Lu, Shiguang Shan, Yonggang Qi, Xinlong Wang Backdooring Vision-Language Models with Out-of-Distribution Data
Weimin Lyu, Jiachen Yao, Saumya Gupta, Lu Pang, Tao Sun, Lingjie Yi, Lijie Hu, Haibin Ling, Chao Chen Backtracking Improves Generation Safety
Yiming Zhang, Jianfeng Chi, Hailey Nguyen, Kartikeya Upasani, Daniel M. Bikel, Jason E Weston, Eric Michael Smith BadRobot: Jailbreaking Embodied LLM Agents in the Physical World
Hangtao Zhang, Chenyu Zhu, Xianlong Wang, Ziqi Zhou, Changgan Yin, Minghui Li, Lulu Xue, Yichen Wang, Shengshan Hu, Aishan Liu, Peijin Guo, Leo Yu Zhang Balancing Act: Diversity and Consistency in Large Language Model Ensembles
Ahmed Abdulaal, Chen Jin, Nina Montaña-Brown, Aryo Pradipta Gema, Daniel C. Castro, Daniel C. Alexander, Philip Alexander Teare, Tom Diethe, Dino Oglic, Amrutha Saseendran BALROG: Benchmarking Agentic LLM and VLM Reasoning on Games
Davide Paglieri, Bartłomiej Cupiał, Samuel Coward, Ulyana Piterbarg, Maciej Wolczyk, Akbir Khan, Eduardo Pignatelli, Łukasz Kuciński, Lerrel Pinto, Rob Fergus, Jakob Nicolaus Foerster, Jack Parker-Holder, Tim Rocktäschel Bandit Learning in Matching Markets with Indifference
Fang Kong, Jingqi Tang, Mingzhu Li, Pinyan Lu, John C.S. Lui, Shuai Li Bayesian Analysis of Combinatorial Gaussian Process Bandits
Jack Sandberg, Niklas Åkerblom, Morteza Haghir Chehreghani Bayesian Experimental Design via Contrastive Diffusions
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez, Florence Forbes Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
Alan Nawzad Amin, Nate Gruver, Yilun Kuang, Yucen Lily Li, Hunter Elliott, Calvin McCarter, Aniruddh Raghu, Peyton Greenside, Andrew Gordon Wilson Bayesian Optimization via Continual Variational Last Layer Training
Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek, James Harrison Bayesian Regularization of Latent Representation
Chukwudi Paul Obite, Zhi Chang, Keyan Wu, Shiwei Lan Benchmarking Agentic Workflow Generation
Shuofei Qiao, Runnan Fang, Zhisong Qiu, Xiaobin Wang, Ningyu Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen Benchmarking LLMs' Judgments with No Gold Standard
Shengwei Xu, Yuxuan Lu, Grant Schoenebeck, Yuqing Kong Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-Adaptive Planning Agent
Yangning Li, Yinghui Li, Xinyu Wang, Yong Jiang, Zhen Zhang, Xinran Zheng, Hui Wang, Hai-Tao Zheng, Fei Huang, Jingren Zhou, Philip S. Yu Benchmarking Predictive Coding Networks -- Made Simple
Luca Pinchetti, Chang Qi, Oleh Lokshyn, Cornelius Emde, Amine M'Charrak, Mufeng Tang, Simon Frieder, Bayar Menzat, Gaspard Oliviers, Rafal Bogacz, Thomas Lukasiewicz, Tommaso Salvatori Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset
Yingzi Ma, Jiongxiao Wang, Fei Wang, Siyuan Ma, Jiazhao Li, Jinsheng Pan, Xiujun Li, Furong Huang, Lichao Sun, Bo Li, Yejin Choi, Muhao Chen, Chaowei Xiao Better Autoregressive Regression with LLMs via Regression-Aware Fine-Tuning
Michal Lukasik, Zhao Meng, Harikrishna Narasimhan, Yin-Wen Chang, Aditya Krishna Menon, Felix Yu, Sanjiv Kumar Better Instruction-Following Through Minimum Bayes Risk
Ian Wu, Patrick Fernandes, Amanda Bertsch, Seungone Kim, Sina Khoshfetrat Pakazad, Graham Neubig Beware of Calibration Data for Pruning Large Language Models
Yixin Ji, Yang Xiang, Juntao Li, Qingrong Xia, Ping Li, Xinyu Duan, Zhefeng Wang, Min Zhang Beyond Autoregression: Discrete Diffusion for Complex Reasoning and Planning
Jiacheng Ye, Jiahui Gao, Shansan Gong, Lin Zheng, Xin Jiang, Zhenguo Li, Lingpeng Kong Beyond Content Relevance: Evaluating Instruction Following in Retrieval Models
Jianqun Zhou, Yuanlei Zheng, Wei Chen, Qianqian Zheng, Shang Zeyuan, Wei Zhang, Rui Meng, Xiaoyu Shen Beyond FVD: An Enhanced Evaluation Metrics for Video Generation Distribution Quality
Ge Ya Luo, Gian Mario Favero, ZhiHao Luo, Alexia Jolicoeur-Martineau, Christopher Pal Beyond Graphs: Can Large Language Models Comprehend Hypergraphs?
Yifan Feng, Chengwu Yang, Xingliang Hou, Shaoyi Du, Shihui Ying, Zongze Wu, Yue Gao Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
Qi Zhang, Yifei Wang, Jingyi Cui, Xiang Pan, Qi Lei, Stefanie Jegelka, Yisen Wang Beyond Random Augmentations: Pretraining with Hard Views
Fabio Ferreira, Ivo Rapant, Jörg K.H. Franke, Frank Hutter BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions
Terry Yue Zhuo, Vu Minh Chien, Jenny Chim, Han Hu, Wenhao Yu, Ratnadira Widyasari, Imam Nur Bani Yusuf, Haolan Zhan, Junda He, Indraneil Paul, Simon Brunner, Chen Gong, James Hoang, Armel Randy Zebaze, Xiaoheng Hong, Wen-Ding Li, Jean Kaddour, Ming Xu, Zhihan Zhang, Prateek Yadav, Naman Jain, Alex Gu, Zhoujun Cheng, Jiawei Liu, Qian Liu, Zijian Wang, Binyuan Hui, Niklas Muennighoff, David Lo, Daniel Fried, Xiaoning Du, Harm de Vries, Leandro Von Werra BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks
Juan A. Rodriguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte Suresh, François Savard, Ahmed Masry, Shravan Nayak, Rabiul Awal, Mahsa Massoud, Amirhossein Abaskohi, Zichao Li, Suyuchen Wang, Pierre-Andre Noel, Mats Leon Richter, Saverio Vadacchino, Shubham Agarwal, Sanket Biswas, Sara Shanian, Ying Zhang, Sathwik Tejaswi Madhusudhan, Joao Monteiro, Krishnamurthy Dj Dvijotham, Torsten Scholak, Nicolas Chapados, Sepideh Kharaghani, Sean Hughes, M. Özsu, Siva Reddy, Marco Pedersoli, Yoshua Bengio, Christopher Pal, Issam H. Laradji, Spandana Gella, Perouz Taslakian, David Vazquez, Sai Rajeswar Bilinear MLPs Enable Weight-Based Mechanistic Interpretability
Michael T Pearce, Thomas Dooms, Alice Rigg, Jose Oramas, Lee Sharkey BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models
Xingyu Zheng, Xianglong Liu, Haotong Qin, Xudong Ma, Mingyuan Zhang, Haojie Hao, Jiakai Wang, Zixiang Zhao, Jinyang Guo, Michele Magno BingoGuard: LLM Content Moderation Tools with Risk Levels
Fan Yin, Philippe Laban, Xiangyu Peng, Yilun Zhou, Yixin Mao, Vaibhav Vats, Linnea Ross, Divyansh Agarwal, Caiming Xiong, Chien-Sheng Wu Bio-xLSTM: Generative Modeling, Representation and In-Context Learning of Biological and Chemical Sequences
Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments
Yusuf H Roohani, Andrew H. Lee, Qian Huang, Jian Vora, Zachary Steinhart, Kexin Huang, Alexander Marson, Percy Liang, Jure Leskovec Biologically Plausible Brain Graph Transformer
Ciyuan Peng, Yuelong Huang, Qichao Dong, Shuo Yu, Feng Xia, Chengqi Zhang, Yaochu Jin BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics
Lukas Rauch, Raphael Schwinger, Moritz Wirth, René Heinrich, Denis Huseljic, Marek Herde, Jonas Lange, Stefan Kahl, Bernhard Sick, Sven Tomforde, Christoph Scholz Black-Box Detection of Language Model Watermarks
Thibaud Gloaguen, Nikola Jovanović, Robin Staab, Martin Vechev BlendRL: A Framework for Merging Symbolic and Neural Policy Learning
Hikaru Shindo, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
Marianne Arriola, Aaron Gokaslan, Justin T Chiu, Zhihan Yang, Zhixuan Qi, Jiaqi Han, Subham Sekhar Sahoo, Volodymyr Kuleshov Block Verification Accelerates Speculative Decoding
Ziteng Sun, Uri Mendlovic, Yaniv Leviathan, Asaf Aharoni, Jae Hun Ro, Ahmad Beirami, Ananda Theertha Suresh BodyGen: Advancing Towards Efficient Embodiment Co-Design
Haofei Lu, Zhe Wu, Junliang Xing, Jianshu Li, Ruoyu Li, Zhe Li, Yuanchun Shi Boltzmann Priors for Implicit Transfer Operators
Juan Viguera Diez, Mathias Jacob Schreiner, Ola Engkvist, Simon Olsson BOND: Aligning LLMs with Best-of-N Distillation
Pier Giuseppe Sessa, Robert Dadashi-Tazehozi, Leonard Hussenot, Johan Ferret, Nino Vieillard, Alexandre Rame, Bobak Shahriari, Sarah Perrin, Abram L. Friesen, Geoffrey Cideron, Sertan Girgin, Piotr Stanczyk, Andrea Michi, Danila Sinopalnikov, Sabela Ramos Garea, Amélie Héliou, Aliaksei Severyn, Matthew Hoffman, Nikola Momchev, Olivier Bachem Bonsai: Gradient-Free Graph Condensation for Node Classification
Mridul Gupta, Samyak Jain, Vansh Ramani, Hariprasad Kodamana, Sayan Ranu Boosting Latent Diffusion with Perceptual Objectives
Tariq Berrada, Pietro Astolfi, Melissa Hall, Marton Havasi, Yohann Benchetrit, Adriana Romero-Soriano, Karteek Alahari, Michal Drozdzal, Jakob Verbeek Boosting Multiple Views for Pretrained-Based Continual Learning
Quyen Tran, Tung Lam Tran, Khanh Doan, Toan Tran, Dinh Phung, Khoat Than, Trung Le Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems
Fu Luo, Xi Lin, Yaoxin Wu, Zhenkun Wang, Tong Xialiang, Mingxuan Yuan, Qingfu Zhang Bootstrapped Model Predictive Control
Yuhang Wang, Hanwei Guo, Sizhe Wang, Long Qian, Xuguang Lan Bootstrapping Language Models with DPO Implicit Rewards
Changyu Chen, Zichen Liu, Chao Du, Tianyu Pang, Qian Liu, Arunesh Sinha, Pradeep Varakantham, Min Lin Bootstrapping Language-Guided Navigation Learning with Self-Refining Data Flywheel
Zun Wang, Jialu Li, Yicong Hong, Songze Li, Kunchang Li, Shoubin Yu, Yi Wang, Yu Qiao, Yali Wang, Mohit Bansal, Limin Wang Both Ears Wide Open: Towards Language-Driven Spatial Audio Generation
Peiwen Sun, Sitong Cheng, Xiangtai Li, Zhen Ye, Huadai Liu, Honggang Zhang, Wei Xue, Yike Guo Brain Mapping with Dense Features: Grounding Cortical Semantic Selectivity in Natural Images with Vision Transformers
Andrew Luo, Jacob Yeung, Rushikesh Zawar, Shaurya Rajat Dewan, Margaret Marie Henderson, Leila Wehbe, Michael J. Tarr BrainOOD: Out-of-Distribution Generalizable Brain Network Analysis
Jiaxing Xu, Yongqiang Chen, Xia Dong, Mengcheng Lan, Tiancheng Huang, Qingtian Bian, James Cheng, Yiping Ke Breaking Neural Network Scaling Laws with Modularity
Akhilan Boopathy, Sunshine Jiang, William Yue, Jaedong Hwang, Abhiram Iyer, Ila R Fiete Breaking the Reclustering Barrier in Centroid-Based Deep Clustering
Lukas Miklautz, Timo Klein, Kevin Sidak, Collin Leiber, Thomas Lang, Andrii Shkabrii, Sebastian Tschiatschek, Claudia Plant Bridging and Modeling Correlations in Pairwise Data for Direct Preference Optimization
Yuxin Jiang, Bo Huang, Yufei Wang, Xingshan Zeng, Liangyou Li, Yasheng Wang, Xin Jiang, Lifeng Shang, Ruiming Tang, Wei Wang Bridging Compressed Image Latents and Multimodal Large Language Models
Chia-Hao Kao, Cheng Chien, Yu-Jen Tseng, Yi-Hsin Chen, Alessandro Gnutti, Shao-Yuan Lo, Wen-Hsiao Peng, Riccardo Leonardi Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding
Yanming Liu, Xinyue Peng, Jiannan Cao, Shi Bo, Yanxin Shen, Tianyu Du, Sheng Cheng, Xun Wang, Jianwei Yin, Xuhong Zhang Bridging Information Asymmetry in Text-Video Retrieval: A Data-Centric Approach
Zechen Bai, Tianjun Xiao, Tong He, Pichao Wang, Zheng Zhang, Thomas Brox, Mike Zheng Shou Bridging the Data Provenance Gap Across Text, Speech, and Video
Shayne Longpre, Nikhil Singh, Manuel Cherep, Kushagra Tiwary, Joanna Materzynska, William Brannon, Robert Mahari, Naana Obeng-Marnu, Manan Dey, Mohammed Hamdy, Nayan Saxena, Ahmad Mustafa Anis, Emad A. Alghamdi, Vu Minh Chien, Da Yin, Kun Qian, Yizhi Li, Minnie Liang, An Dinh, Shrestha Mohanty, Deividas Mataciunas, Tobin South, Jianguo Zhang, Ariel N. Lee, Campbell S. Lund, Christopher Klamm, Damien Sileo, Diganta Misra, Enrico Shippole, Kevin Klyman, Lester James Validad Miranda, Niklas Muennighoff, Seonghyeon Ye, Seungone Kim, Vipul Gupta, Vivek Sharma, Xuhui Zhou, Caiming Xiong, Luis Villa, Stella Biderman, Alex Pentland, Sara Hooker, Jad Kabbara Bridging the Gap Between Database Search and \emph{De Novo} Peptide Sequencing with SearchNovo
Jun Xia, Sizhe Liu, Jingbo Zhou, Shaorong Chen, Hongxin Xiang, Zicheng Liu, Yue Liu, Stan Z. Li Bridging the Semantic Gap Between Text and Table: A Case Study on NL2SQL
Lin Long, Xijun Gu, Xinjie Sun, Wentao Ye, Haobo Wang, Sai Wu, Gang Chen, Junbo Zhao BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval
Hongjin Su, Howard Yen, Mengzhou Xia, Weijia Shi, Niklas Muennighoff, Han-yu Wang, Liu Haisu, Quan Shi, Zachary S Siegel, Michael Tang, Ruoxi Sun, Jinsung Yoon, Sercan O Arik, Danqi Chen, Tao Yu Bringing NeRFs to the Latent Space: Inverse Graphics Autoencoder
Antoine Schnepf, Karim Kassab, Jean-Yves Franceschi, Laurent Caraffa, Flavian Vasile, Jeremie Mary, Andrew I. Comport, Valerie Gouet-Brunet Building Math Agents with Multi-Turn Iterative Preference Learning
Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, Tianqi Liu Bundle Neural Network for Message Diffusion on Graphs
Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein Cached Multi-LoRA Composition for Multi-Concept Image Generation
Xiandong Zou, Mingzhu Shen, Christos-Savvas Bouganis, Yiren Zhao Cafe-Talk: Generating 3D Talking Face Animation with Multimodal Coarse- and Fine-Grained Control
Hejia Chen, Haoxian Zhang, Shoulong Zhang, Xiaoqiang Liu, Sisi Zhuang, Zhangyuan, Pengfei Wan, Di Zhang, Shuai Li CAKE: Cascading and Adaptive KV Cache Eviction with Layer Preferences
Ziran Qin, Yuchen Cao, Mingbao Lin, Wen Hu, Shixuan Fan, Ke Cheng, Weiyao Lin, Jianguo Li Calibrating Expressions of Certainty
Peiqi Wang, Barbara D. Lam, Yingcheng Liu, Ameneh Asgari-Targhi, Rameswar Panda, William M Wells, Tina Kapur, Polina Golland CameraCtrl: Enabling Camera Control for Video Diffusion Models
Hao He, Yinghao Xu, Yuwei Guo, Gordon Wetzstein, Bo Dai, Hongsheng Li, Ceyuan Yang CAMEx: Curvature-Aware Merging of Experts
Viet Dung Nguyen, Minh Nguyen Hoang, Luc Nguyen, Rachel Teo, Tan Minh Nguyen, Linh Duy Tran Can a Large Language Model Be a Gaslighter?
Wei Li, Luyao Zhu, Yang Song, Ruixi Lin, Rui Mao, Yang You Can Knowledge Editing Really Correct Hallucinations?
Baixiang Huang, Canyu Chen, Xiongxiao Xu, Ali Payani, Kai Shu Can Large Language Models Understand Symbolic Graphics Programs?
Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf Can LLMs Separate Instructions from Data? and What Do We Even Mean by That?
Egor Zverev, Sahar Abdelnabi, Soroush Tabesh, Mario Fritz, Christoph H. Lampert Can LLMs Solve Longer Math Word Problems Better?
Xin Xu, Tong Xiao, Zitong Chao, Zhenya Huang, Can Yang, Yang Wang Can Textual Gradient Work in Federated Learning?
Minghui Chen, Ruinan Jin, Wenlong Deng, Yuanyuan Chen, Zhi Huang, Han Yu, Xiaoxiao Li Can Transformers Do Enumerative Geometry?
Baran Hashemi, Roderic Guigo Corominas, Alessandro Giacchetto Can Watermarked LLMs Be Identified by Users via Crafted Prompts?
Aiwei Liu, Sheng Guan, Yiming Liu, Leyi Pan, Yifei Zhang, Liancheng Fang, Lijie Wen, Philip S. Yu, Xuming Hu Can Watermarks Be Used to Detect LLM IP Infringement for Free?
Zhengyue Zhao, Xiaogeng Liu, Somesh Jha, Patrick McDaniel, Bo Li, Chaowei Xiao Can We Talk Models into Seeing the World Differently?
Paul Gavrikov, Jovita Lukasik, Steffen Jung, Robert Geirhos, Muhammad Jehanzeb Mirza, Margret Keuper, Janis Keuper CaPo: Cooperative Plan Optimization for Efficient Embodied Multi-Agent Cooperation
Jie Liu, Pan Zhou, Yingjun Du, Ah-Hwee Tan, Cees G. M. Snoek, Jan-Jakob Sonke, Efstratios Gavves Captured by Captions: On Memorization and Its Mitigation in CLIP Models
Wenhao Wang, Adam Dziedzic, Grace C. Kim, Michael Backes, Franziska Boenisch Capturing the Temporal Dependence of Training Data Influence
Jiachen T. Wang, Dawn Song, James Zou, Prateek Mittal, Ruoxi Jia CAT-3DGS: A Context-Adaptive Triplane Approach to Rate-Distortion-Optimized 3DGS Compression
Yu-Ting Zhan, Cheng-Yuan Ho, Hebi Yang, Yi-Hsin Chen, Jui Chiu Chiang, Yu-Lun Liu, Wen-Hsiao Peng Catastrophic Failure of LLM Unlearning via Quantization
Zhiwei Zhang, Fali Wang, Xiaomin Li, Zongyu Wu, Xianfeng Tang, Hui Liu, Qi He, Wenpeng Yin, Suhang Wang CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching
Xingjian Wu, Xiangfei Qiu, Zhengyu Li, Yihang Wang, Jilin Hu, Chenjuan Guo, Hui Xiong, Bin Yang CatVTON: Concatenation Is All You Need for Virtual Try-on with Diffusion Models
Zheng Chong, Xiao Dong, Haoxiang Li, Shiyue Zhang, Wenqing Zhang, Hanqing Zhao, Xujie Zhang, Dongmei Jiang, Xiaodan Liang Cauchy-Schwarz Regularizers
Sueda Taner, Ziyi Wang, Christoph Studer Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning
Gabriele Dominici, Pietro Barbiero, Mateo Espinosa Zarlenga, Alberto Termine, Martin Gjoreski, Giuseppe Marra, Marc Langheinrich Causal Graphical Models for Vision-Language Compositional Understanding
Fiorenzo Parascandolo, Nicholas Moratelli, Enver Sangineto, Lorenzo Baraldi, Rita Cucchiara Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference
Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar, Saketh Bachu, Vineeth N. Balasubramanian, Amit Sharma Causal Representation Learning from Multimodal Biomedical Observations
Yuewen Sun, Lingjing Kong, Guangyi Chen, Loka Li, Gongxu Luo, Zijian Li, Yixuan Zhang, Yujia Zheng, Mengyue Yang, Petar Stojanov, Eran Segal, Eric P. Xing, Kun Zhang Causally Motivated Sycophancy Mitigation for Large Language Models
Haoxi Li, Xueyang Tang, Jie Zhang, Song Guo, Sikai Bai, Peiran Dong, Yue Yu CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph
Haitao Lin, Guojiang Zhao, Odin Zhang, Yufei Huang, Lirong Wu, Cheng Tan, Zicheng Liu, Zhifeng Gao, Stan Z. Li CBQ: Cross-Block Quantization for Large Language Models
Xin Ding, Xiaoyu Liu, Zhijun Tu, Yun Zhang, Wei Li, Jie Hu, Hanting Chen, Yehui Tang, Zhiwei Xiong, Baoqun Yin, Yunhe Wang CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding
Jiquan Wang, Sha Zhao, Zhiling Luo, Yangxuan Zhou, Haiteng Jiang, Shijian Li, Tao Li, Gang Pan Centrality-Guided Pre-Training for Graph
Bin Liang, Shiwei Chen, Lin Gui, Hui Wang, Yue Yu, Ruifeng Xu, Kam-Fai Wong Century: A Framework and Dataset for Evaluating Historical Contextualisation of Sensitive Images
Canfer Akbulut, Kevin Robinson, Maribeth Rauh, Isabela Albuquerque, Olivia Wiles, Laura Weidinger, Verena Rieser, Yana Hasson, Nahema Marchal, Iason Gabriel, William Isaac, Lisa Anne Hendricks CertainlyUncertain: A Benchmark and Metric for Multimodal Epistemic and Aleatoric Awareness
Khyathi Chandu, Linjie Li, Anas Awadalla, Ximing Lu, Jae Sung Park, Jack Hessel, Lijuan Wang, Yejin Choi Certifying Counterfactual Bias in LLMs
Isha Chaudhary, Qian Hu, Manoj Kumar, Morteza Ziyadi, Rahul Gupta, Gagandeep Singh CG-Bench: Clue-Grounded Question Answering Benchmark for Long Video Understanding
Guo Chen, Yicheng Liu, Yifei Huang, Baoqi Pei, Jilan Xu, Yuping He, Tong Lu, Yali Wang, Limin Wang Charting the Design Space of Neural Graph Representations for Subgraph Matching
Vaibhav Raj, Indradyumna Roy, Ashwin Ramachandran, Soumen Chakrabarti, Abir De ChartMimic: Evaluating LMM's Cross-Modal Reasoning Capability via Chart-to-Code Generation
Cheng Yang, Chufan Shi, Yaxin Liu, Bo Shui, Junjie Wang, Mohan Jing, Linran Xu, Xinyu Zhu, Siheng Li, Yuxiang Zhang, Gongye Liu, Xiaomei Nie, Deng Cai, Yujiu Yang CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL
Mohammadreza Pourreza, Hailong Li, Ruoxi Sun, Yeounoh Chung, Shayan Talaei, Gaurav Tarlok Kakkar, Yu Gan, Amin Saberi, Fatma Ozcan, Sercan O Arik ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities
Peng Xu, Wei Ping, Xianchao Wu, Chejian Xu, Zihan Liu, Mohammad Shoeybi, Bryan Catanzaro ChemAgent: Self-Updating Memories in Large Language Models Improves Chemical Reasoning
Xiangru Tang, Tianyu Hu, Muyang Ye, Yanjun Shao, Xunjian Yin, Siru Ouyang, Wangchunshu Zhou, Pan Lu, Zhuosheng Zhang, Yilun Zhao, Arman Cohan, Mark Gerstein Chemistry-Inspired Diffusion with Non-Differentiable Guidance
Yuchen Shen, Chenhao Zhang, Sijie Fu, Chenghui Zhou, Newell Washburn, Barnabas Poczos CHiP: Cross-Modal Hierarchical Direct Preference Optimization for Multimodal LLMs
Jinlan Fu, Huangfushenzhen, Hao Fei, Xiaoyu Shen, Bryan Hooi, Xipeng Qiu, See-Kiong Ng Chunk-Distilled Language Modeling
Yanhong Li, Karen Livescu, Jiawei Zhou CipherPrune: Efficient and Scalable Private Transformer Inference
Yancheng Zhang, Jiaqi Xue, Mengxin Zheng, Mimi Xie, Mingzhe Zhang, Lei Jiang, Qian Lou CityAnchor: City-Scale 3D Visual Grounding with Multi-Modality LLMs
Jinpeng Li, Haiping Wang, Jiabin Chen, Yuan Liu, Zhiyang Dou, Yuexin Ma, Sibei Yang, Yuan Li, Wenping Wang, Zhen Dong, Bisheng Yang CL-DiffPhyCon: Closed-Loop Diffusion Control of Complex Physical Systems
Long Wei, Haodong Feng, Yuchen Yang, Ruiqi Feng, Peiyan Hu, Xiang Zheng, Tao Zhang, Dixia Fan, Tailin Wu ClassDiffusion: More Aligned Personalization Tuning with Explicit Class Guidance
Jiannan Huang, Jun Hao Liew, Hanshu Yan, Yuyang Yin, Yao Zhao, Humphrey Shi, Yunchao Wei CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at Scale
ZeMing Gong, Austin Wang, Xiaoliang Huo, Joakim Bruslund Haurum, Scott C. Lowe, Graham W. Taylor, Angel X Chang ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models
Veeramakali Vignesh Manivannan, Yasaman Jafari, Srikar Eranky, Spencer Ho, Rose Yu, Duncan Watson-Parris, Yian Ma, Leon Bergen, Taylor Berg-Kirkpatrick CLoSD: Closing the Loop Between Simulation and Diffusion for Multi-Task Character Control
Guy Tevet, Sigal Raab, Setareh Cohan, Daniele Reda, Zhengyi Luo, Xue Bin Peng, Amit Haim Bermano, Michiel van de Panne Closed-Form Merging of Parameter-Efficient Modules for Federated Continual Learning
Riccardo Salami, Pietro Buzzega, Matteo Mosconi, Jacopo Bonato, Luigi Sabetta, Simone Calderara Co$^{\mathbf{3}}$Gesture: Towards Coherent Concurrent Co-Speech 3D Gesture Generation with Interactive Diffusion
Xingqun Qi, Yatian Wang, Hengyuan Zhang, Jiahao Pan, Wei Xue, Shanghang Zhang, Wenhan Luo, Qifeng Liu, Yike Guo Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusion
Minkyoung Cho, Yulong Cao, Jiachen Sun, Qingzhao Zhang, Marco Pavone, Jeong Joon Park, Heng Yang, Zhuoqing Mao CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs
Dung Manh Nguyen, Thang Chau Phan, Nam Le Hai, Tien-Thong Doan, Nam V. Nguyen, Quang Pham, Nghi D. Q. Bui CofCA: A STEP-WISE Counterfactual Multi-Hop QA Benchmark
Jian Wu, Linyi Yang, Zhen Wang, Manabu Okumura, Yue Zhang CogCoM: A Visual Language Model with Chain-of-Manipulations Reasoning
Ji Qi, Ming Ding, Weihan Wang, Yushi Bai, Qingsong Lv, Wenyi Hong, Bin Xu, Lei Hou, Juanzi Li, Yuxiao Dong, Jie Tang CogVideoX: Text-to-Video Diffusion Models with an Expert Transformer
Zhuoyi Yang, Jiayan Teng, Wendi Zheng, Ming Ding, Shiyu Huang, Jiazheng Xu, Yuanming Yang, Wenyi Hong, Xiaohan Zhang, Guanyu Feng, Da Yin, Yuxuan.Zhang, Weihan Wang, Yean Cheng, Bin Xu, Xiaotao Gu, Yuxiao Dong, Jie Tang Collab: Controlled Decoding Using Mixture of Agents for LLM Alignment
Souradip Chakraborty, Sujay Bhatt, Udari Madhushani Sehwag, Soumya Suvra Ghosal, Jiahao Qiu, Mengdi Wang, Dinesh Manocha, Furong Huang, Alec Koppel, Sumitra Ganesh CollabEdit: Towards Non-Destructive Collaborative Knowledge Editing
Jiamu Zheng, Jinghuai Zhang, Tianyu Du, Xuhong Zhang, Jianwei Yin, Tao Lin Collapsed Language Models Promote Fairness
Jingxuan Xu, Wuyang Chen, Linyi Li, Yao Zhao, Yunchao Wei ColPali: Efficient Document Retrieval with Vision Language Models
Manuel Faysse, Hugues Sibille, Tony Wu, Bilel Omrani, Gautier Viaud, Celine Hudelot, Pierre Colombo Combatting Dimensional Collapse in LLM Pre-Training Data via Submodular File Selection
Ziqing Fan, Siyuan Du, Shengchao Hu, Pingjie Wang, Li Shen, Ya Zhang, Dacheng Tao, Yanfeng Wang Combining Induction and Transduction for Abstract Reasoning
Wen-Ding Li, Keya Hu, Carter Larsen, Yuqing Wu, Simon Alford, Caleb Woo, Spencer M. Dunn, Hao Tang, Wei-Long Zheng, Yewen Pu, Kevin Ellis COMBO: Compositional World Models for Embodied Multi-Agent Cooperation
Hongxin Zhang, Zeyuan Wang, Qiushi Lyu, Zheyuan Zhang, Sunli Chen, Tianmin Shu, Behzad Dariush, Kwonjoon Lee, Yilun Du, Chuang Gan COME: Test-Time Adaption by Conservatively Minimizing Entropy
Qingyang Zhang, Yatao Bian, Xinke Kong, Peilin Zhao, Changqing Zhang Commit0: Library Generation from Scratch
Wenting Zhao, Nan Jiang, Celine Lee, Justin T Chiu, Claire Cardie, Matthias Gallé, Alexander M Rush CoMotion: Concurrent Multi-Person 3D Motion
Alejandro Newell, Peiyun Hu, Lahav Lipson, Stephan Richter, Vladlen Koltun Competing Large Language Models in Multi-Agent Gaming Environments
Jen-tse Huang, Eric John Li, Man Ho Lam, Tian Liang, Wenxuan Wang, Youliang Yuan, Wenxiang Jiao, Xing Wang, Zhaopeng Tu, Michael Lyu Competitive Fair Scheduling with Predictions
Tianming Zhao, Chunqiu Xia, Xiaomin Chang, Chunhao Li, Wei Li, Albert Zomaya Composable Interventions for Language Models
Arinbjörn Kolbeinsson, Kyle O'Brien, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Jayant Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen Composing Unbalanced Flows for Flexible Docking and Relaxation
Gabriele Corso, Vignesh Ram Somnath, Noah Getz, Regina Barzilay, Tommi Jaakkola, Andreas Krause Compositional Entailment Learning for Hyperbolic Vision-Language Models
Avik Pal, Max van Spengler, Guido Maria D'Amely di Melendugno, Alessandro Flaborea, Fabio Galasso, Pascal Mettes Compositional Simulation-Based Inference for Time Series
Manuel Gloeckler, Shoji Toyota, Kenji Fukumizu, Jakob H. Macke Computational Explorations of Total Variation Distance
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran Compute-Optimal LLMs Provably Generalize Better with Scale
Marc Anton Finzi, Sanyam Kapoor, Diego Granziol, Anming Gu, Christopher De Sa, J Zico Kolter, Andrew Gordon Wilson Computing Circuits Optimization via Model-Based Circuit Genetic Evolution
Zhihai Wang, Jie Wang, Xilin Xia, Dongsheng Zuo, Lei Chen, Yuzhe Ma, Jianye Hao, Mingxuan Yuan, Feng Wu Concept Bottleneck Language Models for Protein Design
Aya Abdelsalam Ismail, Tuomas Oikarinen, Amy Wang, Julius Adebayo, Samuel Don Stanton, Hector Corrada Bravo, Kyunghyun Cho, Nathan C. Frey Concept Bottleneck Large Language Models
Chung-En Sun, Tuomas Oikarinen, Berk Ustun, Tsui-Wei Weng Conformal Language Model Reasoning with Coherent Factuality
Maxon Rubin-Toles, Maya Gambhir, Keshav Ramji, Aaron Roth, Surbhi Goel Conformal Prediction Sets Can Cause Disparate Impact
Jesse C. Cresswell, Bhargava Kumar, Yi Sui, Mouloud Belbahri Conformal Structured Prediction
Botong Zhang, Shuo Li, Osbert Bastani Conformalized Survival Analysis for General Right-Censored Data
Hen Davidov, Shai Feldman, Gil Shamai, Ron Kimmel, Yaniv Romano CONGO: Compressive Online Gradient Optimization
Jeremy Carleton, Prathik Vijaykumar, Divyanshu Saxena, Dheeraj Narasimha, Srinivas Shakkottai, Aditya Akella Connecting Federated ADMM to Bayes
Siddharth Swaroop, Mohammad Emtiyaz Khan, Finale Doshi-Velez Consistency Checks for Language Model Forecasters
Daniel Paleka, Abhimanyu Pallavi Sudhir, Alejandro Alvarez, Vineeth Bhat, Adam Shen, Evan Wang, Florian Tramèr Consistency Models Made Easy
Zhengyang Geng, Ashwini Pokle, Weijian Luo, Justin Lin, J Zico Kolter Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets
Yuxin Wang, Maresa Schröder, Dennis Frauen, Jonas Schweisthal, Konstantin Hess, Stefan Feuerriegel Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHR Data
Michael Wornow, Suhana Bedi, Miguel Angel Fuentes Hernandez, Ethan Steinberg, Jason Alan Fries, Christopher Re, Sanmi Koyejo, Nigam Shah Context Steering: Controllable Personalization at Inference Time
Jerry Zhi-Yang He, Sashrika Pandey, Mariah L Schrum, Anca Dragan Context-Aware Dynamic Pruning for Speech Foundation Models
Masao Someki, Yifan Peng, Siddhant Arora, Markus Müller, Athanasios Mouchtaris, Grant Strimel, Jing Liu, Shinji Watanabe ContextGNN: Beyond Two-Tower Recommendation Systems
Yiwen Yuan, Zecheng Zhang, Xinwei He, Akihiro Nitta, Weihua Hu, Manan Shah, Blaž Stojanovič, Shenyang Huang, Jan Eric Lenssen, Jure Leskovec, Matthias Fey Contextual Document Embeddings
John Xavier Morris, Alexander M Rush Contextualizing Biological Perturbation Experiments Through Language
Menghua Wu, Russell Littman, Jacob Levine, Lin Qiu, Tommaso Biancalani, David Richmond, Jan-Christian Huetter Continuous Ensemble Weather Forecasting with Diffusion Models
Martin Andrae, Tomas Landelius, Joel Oskarsson, Fredrik Lindsten Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery
Amin Abyaneh, Mahrokh Ghoddousi Boroujeni, Hsiu-Chin Lin, Giancarlo Ferrari-Trecate ContraDiff: Planning Towards High Return States via Contrastive Learning
Yixiang Shan, Zhengbang Zhu, Ting Long, Liang Qifan, Yi Chang, Weinan Zhang, Liang Yin ControlAR: Controllable Image Generation with Autoregressive Models
Zongming Li, Tianheng Cheng, Shoufa Chen, Peize Sun, Haocheng Shen, Longjin Ran, Xiaoxin Chen, Wenyu Liu, Xinggang Wang Controllable Context Sensitivity and the Knob Behind It
Julian Minder, Kevin Du, Niklas Stoehr, Giovanni Monea, Chris Wendler, Robert West, Ryan Cotterell Controlling Language and Diffusion Models by Transporting Activations
Pau Rodriguez, Arno Blaas, Michal Klein, Luca Zappella, Nicholas Apostoloff, Marco Cuturi, Xavier Suau Controlling Space and Time with Diffusion Models
Daniel Watson, Saurabh Saxena, Lala Li, Andrea Tagliasacchi, David J. Fleet Coreset Spectral Clustering
Ben Jourdan, Gregory Schwartzman, Peter Macgregor, He Sun CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking
Tarun Suresh, Revanth Gangi Reddy, Yifei Xu, Zach Nussbaum, Andriy Mulyar, Brandon Duderstadt, Heng Ji Correlating Instruction-Tuning (in Multimodal Models) with Vision-Language Processing (in the Brain)
Subba Reddy Oota, Akshett Rai Jindal, Ishani Mondal, Khushbu Pahwa, Satya Sai Srinath Namburi Gnvv, Manish Shrivastava, Maneesh Kumar Singh, Bapi Raju Surampudi, Manish Gupta Counterfactual Concept Bottleneck Models
Gabriele Dominici, Pietro Barbiero, Francesco Giannini, Martin Gjoreski, Giuseppe Marra, Marc Langheinrich Counterfactual Realizability
Arvind Raghavan, Elias Bareinboim CR-CTC: Consistency Regularization on CTC for Improved Speech Recognition
Zengwei Yao, Wei Kang, Xiaoyu Yang, Fangjun Kuang, Liyong Guo, Han Zhu, Zengrui Jin, Zhaoqing Li, Long Lin, Daniel Povey CREAM: Consistency Regularized Self-Rewarding Language Models
Zhaoyang Wang, Weilei He, Zhiyuan Liang, Xuchao Zhang, Chetan Bansal, Ying Wei, Weitong Zhang, Huaxiu Yao Cross the Gap: Exposing the Intra-Modal Misalignment in CLIP via Modality Inversion
Marco Mistretta, Alberto Baldrati, Lorenzo Agnolucci, Marco Bertini, Andrew D. Bagdanov Cross-Domain Offline Policy Adaptation with Optimal Transport and Dataset Constraint
Jiafei Lyu, Mengbei Yan, Zhongjian Qiao, Runze Liu, Xiaoteng Ma, Deheng Ye, Jing-Wen Yang, Zongqing Lu, Xiu Li Cross-Entropy Is All You Need to Invert the Data Generating Process
Patrik Reizinger, Alice Bizeul, Attila Juhos, Julia E Vogt, Randall Balestriero, Wieland Brendel, David Klindt cryoSPHERE: Single-Particle HEterogeneous REconstruction from Cryo EM
Gabriel Ducrocq, Lukas Grunewald, Sebastian Westenhoff, Fredrik Lindsten CS-Bench: A Comprehensive Benchmark for Large Language Models Towards Computer Science Mastery
Xiaoshuai Song, Muxi Diao, Guanting Dong, Zhengyang Wang, Yujia Fu, Runqi Qiao, Zhexu Wang, Dayuan Fu, Huangxuan Wu, Bin Liang, Weihao Zeng, Yejie Wang, Zhuoma GongQue, Jianing Yu, Qiuna Tan, Weiran Xu CubeDiff: Repurposing Diffusion-Based Image Models for Panorama Generation
Nikolai Kalischek, Michael Oechsle, Fabian Manhardt, Philipp Henzler, Konrad Schindler, Federico Tombari CURIE: Evaluating LLMs on Multitask Scientific Long-Context Understanding and Reasoning
Hao Cui, Zahra Shamsi, Gowoon Cheon, Xuejian Ma, Shutong Li, Maria Tikhanovskaya, Peter Christian Norgaard, Nayantara Mudur, Martyna Beata Plomecka, Paul Raccuglia, Yasaman Bahri, Victor V. Albert, Pranesh Srinivasan, Haining Pan, Philippe Faist, Brian A Rohr, Michael J. Statt, Dan Morris, Drew Purves, Elise Kleeman, Ruth Alcantara, Matthew Abraham, Muqthar Mohammad, Ean Phing VanLee, Chenfei Jiang, Elizabeth Dorfman, Eun-Ah Kim, Michael Brenner, Sameera S Ponda, Subhashini Venugopalan Cut the Crap: An Economical Communication Pipeline for LLM-Based Multi-Agent Systems
Guibin Zhang, Yanwei Yue, Zhixun Li, Sukwon Yun, Guancheng Wan, Kun Wang, Dawei Cheng, Jeffrey Xu Yu, Tianlong Chen Cut Your Losses in Large-Vocabulary Language Models
Erik Wijmans, Brody Huval, Alexander Hertzberg, Vladlen Koltun, Philipp Kraehenbuehl CViT: Continuous Vision Transformer for Operator Learning
Sifan Wang, Jacob H Seidman, Shyam Sankaran, Hanwen Wang, George J. Pappas, Paris Perdikaris Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models
Andy K Zhang, Neil Perry, Riya Dulepet, Joey Ji, Celeste Menders, Justin W Lin, Eliot Jones, Gashon Hussein, Samantha Liu, Donovan Julian Jasper, Pura Peetathawatchai, Ari Glenn, Vikram Sivashankar, Daniel Zamoshchin, Leo Glikbarg, Derek Askaryar, Haoxiang Yang, Aolin Zhang, Rishi Alluri, Nathan Tran, Rinnara Sangpisit, Kenny O Oseleononmen, Dan Boneh, Daniel E. Ho, Percy Liang CyberHost: A One-Stage Diffusion Framework for Audio-Driven Talking Body Generation
Gaojie Lin, Jianwen Jiang, Chao Liang, Tianyun Zhong, Jiaqi Yang, Zerong Zheng, Yanbo Zheng CycleResearcher: Improving Automated Research via Automated Review
Yixuan Weng, Minjun Zhu, Guangsheng Bao, Hongbo Zhang, Jindong Wang, Yue Zhang, Linyi Yang DARE the Extreme: Revisiting Delta-Parameter Pruning for Fine-Tuned Models
Wenlong Deng, Yize Zhao, Vala Vakilian, Minghui Chen, Xiaoxiao Li, Christos Thrampoulidis DarkBench: Benchmarking Dark Patterns in Large Language Models
Esben Kran, Hieu Minh Nguyen, Akash Kundu, Sami Jawhar, Jinsuk Park, Mateusz Maria Jurewicz Data Center Cooling System Optimization Using Offline Reinforcement Learning
Xianyuan Zhan, Xiangyu Zhu, Peng Cheng, Xiao Hu, Ziteng He, Hanfei Geng, Jichao Leng, Huiwen Zheng, Chenhui Liu, Tianshun Hong, Yan Liang, Yunxin Liu, Feng Zhao Data Pruning by Information Maximization
Haoru Tan, Sitong Wu, Wei Huang, Shizhen Zhao, Xiaojuan Qi Data Scaling Laws in Imitation Learning for Robotic Manipulation
Fanqi Lin, Yingdong Hu, Pingyue Sheng, Chuan Wen, Jiacheng You, Yang Gao Data Selection via Optimal Control for Language Models
Yuxian Gu, Li Dong, Hongning Wang, Yaru Hao, Qingxiu Dong, Furu Wei, Minlie Huang Data Shapley in One Training Run
Jiachen T. Wang, Prateek Mittal, Dawn Song, Ruoxi Jia Data Unlearning in Diffusion Models
Silas Alberti, Kenan Hasanaliyev, Manav Shah, Stefano Ermon DataGen: Unified Synthetic Dataset Generation via Large Language Models
Yue Huang, Siyuan Wu, Chujie Gao, Dongping Chen, Qihui Zhang, Yao Wan, Tianyi Zhou, Chaowei Xiao, Jianfeng Gao, Lichao Sun, Xiangliang Zhang DataMan: Data Manager for Pre-Training Large Language Models
Ru Peng, Kexin Yang, Yawen Zeng, Junyang Lin, Dayiheng Liu, Junbo Zhao Dataset Ownership Verification in Contrastive Pre-Trained Models
Yuechen Xie, Jie Song, Mengqi Xue, Haofei Zhang, Xingen Wang, Bingde Hu, Genlang Chen, Mingli Song Debiasing Federated Learning with Correlated Client Participation
Zhenyu Sun, Ziyang Zhang, Zheng Xu, Gauri Joshi, Pranay Sharma, Ermin Wei dEBORA: Efficient Bilevel Optimization-Based Low-Rank Adaptation
Emanuele Zangrando, Sara Venturini, Francesco Rinaldi, Francesco Tudisco Decentralized Optimization with Coupled Constraints
Demyan Yarmoshik, Alexander Rogozin, Nikita Kiselev, Daniil Dorin, Alexander Gasnikov, Dmitry Kovalev DeciMamba: Exploring the Length Extrapolation Potential of Mamba
Assaf Ben-Kish, Itamar Zimerman, Shady Abu-Hussein, Nadav Cohen, Amir Globerson, Lior Wolf, Raja Giryes Decision Information Meets Large Language Models: The Future of Explainable Operations Research
Yansen Zhang, Qingcan Kang, Wing Yin Yu, HaileiGong, Xiaojin Fu, Xiongwei Han, Tao Zhong, Chen Ma Decomposition Polyhedra of Piecewise Linear Functions
Marie-Charlotte Brandenburg, Moritz Leo Grillo, Christoph Hertrich Deconstructing What Makes a Good Optimizer for Autoregressive Language Models
Rosie Zhao, Depen Morwani, David Brandfonbrener, Nikhil Vyas, Sham M. Kakade Decoupled Subgraph Federated Learning
Javad Aliakbari, Johan Östman, Alexandre Graell i Amat DEEM: Diffusion Models Serve as the Eyes of Large Language Models for Image Perception
Run Luo, Yunshui Li, Longze Chen, Wanwei He, Ting-En Lin, Ziqiang Liu, Lei Zhang, Zikai Song, Hamid Alinejad-Rokny, Xiaobo Xia, Tongliang Liu, Binyuan Hui, Min Yang Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models
Junyu Chen, Han Cai, Junsong Chen, Enze Xie, Shang Yang, Haotian Tang, Muyang Li, Song Han Deep Distributed Optimization for Large-Scale Quadratic Programming
Augustinos D Saravanos, Hunter Kuperman, Alex Oshin, Arshiya Taj Abdul, Vincent Pacelli, Evangelos Theodorou Deep Kernel Relative Test for Machine-Generated Text Detection
Yiliao Song, Zhenqiao Yuan, Shuhai Zhang, Zhen Fang, Jun Yu, Feng Liu Deep Linear Probe Generators for Weight Space Learning
Jonathan Kahana, Eliahu Horwitz, Imri Shuval, Yedid Hoshen Deep MMD Gradient Flow Without Adversarial Training
Alexandre Galashov, Valentin De Bortoli, Arthur Gretton Deep Networks Learn Features from Local Discontinuities in the Label Function
Prithaj Banerjee, Harish Guruprasad Ramaswamy, Mahesh Lorik Yadav, Chandra Shekar Lakshminarayanan Deep Signature: Characterization of Large-Scale Molecular Dynamics
Tiexin Qin, Mengxu Zhu, Chunyang Li, Terry Lyons, Hong Yan, Haoliang Li DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale
Ziyang Zheng, Shan Huang, Jianyuan Zhong, Zhengyuan Shi, Guohao Dai, Ningyi Xu, Qiang Xu DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search
Huajian Xin, Z.Z. Ren, Junxiao Song, Zhihong Shao, Wanjia Zhao, Haocheng Wang, Bo Liu, Liyue Zhang, Xuan Lu, Qiushi Du, Wenjun Gao, Haowei Zhang, Qihao Zhu, Dejian Yang, Zhibin Gou, Z.F. Wu, Fuli Luo, Chong Ruan DELIFT: Data Efficient Language Model Instruction Fine-Tuning
Ishika Agarwal, Krishnateja Killamsetty, Lucian Popa, Marina Danilevsky DelTA: An Online Document-Level Translation Agent Based on Multi-Level Memory
Yutong Wang, Jiali Zeng, Xuebo Liu, Derek F. Wong, Fandong Meng, Jie Zhou, Min Zhang Delta: Dense Efficient Long-Range 3D Tracking for Any Video
Tuan Duc Ngo, Peiye Zhuang, Evangelos Kalogerakis, Chuang Gan, Sergey Tulyakov, Hsin-Ying Lee, Chaoyang Wang Denoising Autoregressive Transformers for Scalable Text-to-Image Generation
Jiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang, Dinghuai Zhang, Navdeep Jaitly, Joshua M. Susskind, Shuangfei Zhai DenseGrounding: Improving Dense Language-Vision Semantics for Ego-Centric 3D Visual Grounding
Henry Zheng, Hao Shi, Qihang Peng, Yong Xien Chng, Rui Huang, Yepeng Weng, Zhongchao Shi, Gao Huang DEPT: Decoupled Embeddings for Pre-Training Language Models
Alex Iacob, Lorenzo Sani, Meghdad Kurmanji, William F. Shen, Xinchi Qiu, Dongqi Cai, Yan Gao, Nicholas Donald Lane Depth Any Video with Scalable Synthetic Data
Honghui Yang, Di Huang, Wei Yin, Chunhua Shen, Haifeng Liu, Xiaofei He, Binbin Lin, Wanli Ouyang, Tong He Depth Pro: Sharp Monocular Metric Depth in Less than a Second
Alexey Bochkovskiy, Amaël Delaunoy, Hugo Germain, Marcel Santos, Yichao Zhou, Stephan Richter, Vladlen Koltun Designing Mechanical Meta-Materials by Learning Equivariant Flows
Mehran Mirramezani, Anne S. Meeussen, Katia Bertoldi, Peter Orbanz, Ryan P Adams Detecting Backdoor Samples in Contrastive Language Image Pretraining
Hanxun Huang, Sarah Monazam Erfani, Yige Li, Xingjun Ma, James Bailey Determine-Then-Ensemble: Necessity of Top-K Union for Large Language Model Ensembling
Yuxuan Yao, Han Wu, Mingyang Liu, Sichun Luo, Xiongwei Han, Jie Liu, Zhijiang Guo, Linqi Song DICE: End-to-End Deformation Capture of Hand-Face Interactions from a Single Image
Qingxuan Wu, Zhiyang Dou, Sirui Xu, Soshi Shimada, Chen Wang, Zhengming Yu, Yuan Liu, Cheng Lin, Zeyu Cao, Taku Komura, Vladislav Golyanik, Christian Theobalt, Wenping Wang, Lingjie Liu Diff-PIC: Revolutionizing Particle-in-Cell Nuclear Fusion Simulation with Diffusion Models
Chuan Liu, Chunshu Wu, Shihui Cao, Mingkai Chen, James Chenhao Liang, Ang Li, Michael Huang, Chuang Ren, Ying Nian Wu, Dongfang Liu, Tong Geng Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision
Weicai Yan, Wang Lin, Zirun Guo, Ye Wang, Fangming Feng, Xiaoda Yang, Zehan Wang, Tao Jin Difference-of-Submodular Bregman Divergence
Masanari Kimura, Takahiro Kawashima, Tasuku Soma, Hideitsu Hino Differentiable and Learnable Wireless Simulation with Geometric Transformers
Thomas Hehn, Markus Peschl, Tribhuvanesh Orekondy, Arash Behboodi, Johann Brehmer Differentiable Integer Linear Programming
Zijie Geng, Jie Wang, Xijun Li, Fangzhou Zhu, Jianye Hao, Bin Li, Feng Wu Differentiable Optimization of Similarity Scores Between Models and Brains
Nathan Cloos, Moufan Li, Markus Siegel, Scott L Brincat, Earl K Miller, Guangyu Robert Yang, Christopher J Cueva Differentiable Rule Induction from Raw Sequence Inputs
Kun Gao, Katsumi Inoue, Yongzhi Cao, Hanpin Wang, Yang Feng Differential Transformer
Tianzhu Ye, Li Dong, Yuqing Xia, Yutao Sun, Yi Zhu, Gao Huang, Furu Wei Differentially Private Federated Learning with Time-Adaptive Privacy Spending
Shahrzad Kiani, Nupur Kulkarni, Adam Dziedzic, Stark Draper, Franziska Boenisch DiffGAD: A Diffusion-Based Unsupervised Graph Anomaly Detector
Jinghan Li, Yuan Gao, Jinda Lu, Junfeng Fang, Congcong Wen, Hui Lin, Xiang Wang Diffusion Bridge AutoEncoders for Unsupervised Representation Learning
Yeongmin Kim, Kwanghyeon Lee, Minsang Park, Byeonghu Na, Il-chul Moon Diffusion Bridge Implicit Models
Kaiwen Zheng, Guande He, Jianfei Chen, Fan Bao, Jun Zhu Diffusion Feedback Helps CLIP See Better
Wenxuan Wang, Quan Sun, Fan Zhang, Yepeng Tang, Jing Liu, Xinlong Wang Diffusion Models Are Evolutionary Algorithms
Yanbo Zhang, Benedikt Hartl, Hananel Hazan, Michael Levin Diffusion Models Are Real-Time Game Engines
Dani Valevski, Yaniv Leviathan, Moab Arar, Shlomi Fruchter Diffusion Policy Policy Optimization
Allen Z. Ren, Justin Lidard, Lars Lien Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, Max Simchowitz Diffusion Transformers for Tabular Data Time Series Generation
Fabrizio Garuti, Enver Sangineto, Simone Luetto, Lorenzo Forni, Rita Cucchiara Diffusion-Based Neural Network Weights Generation
Bedionita Soro, Bruno Andreis, Hayeon Lee, Wonyong Jeong, Song Chong, Frank Hutter, Sung Ju Hwang Diffusion-Based Planning for Autonomous Driving with Flexible Guidance
Yinan Zheng, Ruiming Liang, Kexin Zheng, Jinliang Zheng, Liyuan Mao, Jianxiong Li, Weihao Gu, Rui Ai, Shengbo Eben Li, Xianyuan Zhan, Jingjing Liu DiffusionGuard: A Robust Defense Against Malicious Diffusion-Based Image Editing
June Suk Choi, Kyungmin Lee, Jongheon Jeong, Saining Xie, Jinwoo Shin, Kimin Lee Dimension Agnostic Neural Processes
Hyungi Lee, Chaeyun Jang, Dong Bok Lee, Juho Lee Directional Gradient Projection for Robust Fine-Tuning of Foundation Models
Chengyue Huang, Junjiao Tian, Brisa Maneechotesuwan, Shivang Chopra, Zsolt Kira Discovering Influential Neuron Path in Vision Transformers
Yifan Wang, Yifei Liu, Yingdong Shi, Changming Li, Anqi Pang, Sibei Yang, Jingyi Yu, Kan Ren DiscoveryBench: Towards Data-Driven Discovery with Large Language Models
Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, Bhavana Dalvi Mishra, Abhijeetsingh Meena, Aryan Prakhar, Tirth Vora, Tushar Khot, Ashish Sabharwal, Peter Clark Discrete Codebook World Models for Continuous Control
Aidan Scannell, Mohammadreza Nakhaeinezhadfard, Kalle Kujanpää, Yi Zhao, Kevin Sebastian Luck, Arno Solin, Joni Pajarinen Discrete Copula Diffusion
Anji Liu, Oliver Broadrick, Mathias Niepert, Guy Van den Broeck Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation
Jun Hyeong Kim, Seonghwan Kim, Seokhyun Moon, Hyeongwoo Kim, Jeheon Woo, Woo Youn Kim Discriminating Image Representations with Principal Distortions
Jenelle Feather, David Lipshutz, Sarah E Harvey, Alex H Williams, Eero P Simoncelli Discriminator-Guided Embodied Planning for LLM Agent
Haofu Qian, Chenjia Bai, Jiatao Zhang, Fei Wu, Wei Song, Xuelong Li Disentangled Representation Learning with the Gromov-Monge Gap
Théo Uscidda, Luca Eyring, Karsten Roth, Fabian J Theis, Zeynep Akata, Marco Cuturi Disentangling 3D Animal Pose Dynamics with Scrubbed Conditional Latent Variables
Joshua Huang Wu, Hari Koneru, James Russell Ravenel, Anshuman Sabath, James Michael Roach, Shaun Sze-Xian Lim, Michael R Tadross, Alex H Williams, Timothy W Dunn DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation
Jing He, Haodong Li, Huyongzhe, Guibao Shen, Yingjie Cai, Weichao Qiu, Ying-Cong Chen DisPose: Disentangling Pose Guidance for Controllable Human Image Animation
Hongxiang Li, Yaowei Li, Yuhang Yang, Junjie Cao, Zhihong Zhu, Xuxin Cheng, Long Chen Dissecting Adversarial Robustness of Multimodal LM Agents
Chen Henry Wu, Rishi Rajesh Shah, Jing Yu Koh, Russ Salakhutdinov, Daniel Fried, Aditi Raghunathan Distance-Based Tree-Sliced Wasserstein Distance
Hoang V. Tran, Minh-Khoi Nguyen-Nhat, Huyen Trang Pham, Thanh Chu, Tam Le, Tan Minh Nguyen Distilling Dataset into Neural Field
Donghyeok Shin, HeeSun Bae, Gyuwon Sim, Wanmo Kang, Il-chul Moon Distilling Structural Representations into Protein Sequence Models
Jeffrey Ouyang-Zhang, Chengyue Gong, Yue Zhao, Philipp Kraehenbuehl, Adam Klivans, Daniel Jesus Diaz Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference
Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Oren Pereg, Moshe Wasserblat, Tomer Galanti, Michal Gordon-Kiwkowitz, David Harel Distribution Backtracking Builds a Faster Convergence Trajectory for Diffusion Distillation
Shengyuan Zhang, Ling Yang, Zejian Li, An Zhao, Chenye Meng, Changyuan Yang, Guang Yang, Zhiyuan Yang, Lingyun Sun Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learning
Hanlin Yang, Jian Yao, Weiming Liu, Qing Wang, Hanmin Qin, Kong Hansheng, Kirk Tang, Jiechao Xiong, Chao Yu, Kai Li, Junliang Xing, Hongwu Chen, Juchao Zhuo, Qiang Fu, Yang Wei, Haobo Fu Diverse Preference Learning for Capabilities and Alignment
Stewart Slocum, Asher Parker-Sartori, Dylan Hadfield-Menell Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents
Kexun Zhang, Weiran Yao, Zuxin Liu, Yihao Feng, Zhiwei Liu, R N Rithesh, Tian Lan, Lei Li, Renze Lou, Jiacheng Xu, Bo Pang, Yingbo Zhou, Shelby Heinecke, Silvio Savarese, Huan Wang, Caiming Xiong Diversity-Rewarded CFG Distillation
Geoffrey Cideron, Andrea Agostinelli, Johan Ferret, Sertan Girgin, Romuald Elie, Olivier Bachem, Sarah Perrin, Alexandre Rame Do Deep Neural Network Solutions Form a Star Domain?
Ankit Sonthalia, Alexander Rubinstein, Ehsan Abbasnejad, Seong Joon Oh Do LLMs ``know'' Internally When They Follow Instructions?
Juyeon Heo, Christina Heinze-Deml, Oussama Elachqar, Kwan Ho Ryan Chan, Shirley You Ren, Andrew Miller, Udhyakumar Nallasamy, Jaya Narain Do LLMs Estimate Uncertainty Well in Instruction-Following?
Juyeon Heo, Miao Xiong, Christina Heinze-Deml, Jaya Narain Do LLMs Have Consistent Values?
Naama Rozen, Liat Bezalel, Gal Elidan, Amir Globerson, Ella Daniel Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex
Tanishq Kumar, Blake Bordelon, Cengiz Pehlevan, Venkatesh N Murthy, Samuel J. Gershman Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts?
Sravanti Addepalli, Yerram Varun, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain Does Spatial Cognition Emerge in Frontier Models?
Santhosh Kumar Ramakrishnan, Erik Wijmans, Philipp Kraehenbuehl, Vladlen Koltun DoF: A Diffusion Factorization Framework for Offline Multi-Agent Reinforcement Learning
Chao Li, Ziwei Deng, Chenxing Lin, Wenqi Chen, Yongquan Fu, Weiquan Liu, Chenglu Wen, Cheng Wang, Siqi Shen Don't Flatten, Tokenize! Unlocking the Key to SoftMoE's Efficacy in Deep RL
Ghada Sokar, Johan Samir Obando Ceron, Aaron Courville, Hugo Larochelle, Pablo Samuel Castro Don’T Stop Me Now: Embedding Based Scheduling for LLMs
Rana Shahout, Eran Malach, Chunwei Liu, Weifan Jiang, Minlan Yu, Michael Mitzenmacher Doubly Robust Identification of Treatment Effects from Multiple Environments
Piersilvio De Bartolomeis, Julia Kostin, Javier Abad, Yixin Wang, Fanny Yang DPaI: Differentiable Pruning at Initialization with Node-Path Balance Principle
Lichuan Xiang, Quan Nguyen-Tri, Lan-Cuong Nguyen, Hoang Pham, Khoat Than, Long Tran-Thanh, Hongkai Wen DPLM-2: A Multimodal Diffusion Protein Language Model
Xinyou Wang, Zaixiang Zheng, Fei Ye, Dongyu Xue, Shujian Huang, Quanquan Gu Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Want
Weifeng Lin, Xinyu Wei, Ruichuan An, Peng Gao, Bocheng Zou, Yulin Luo, Siyuan Huang, Shanghang Zhang, Hongsheng Li Dream to Manipulate: Compositional World Models Empowering Robot Imitation Learning with Imagination
Leonardo Barcellona, Andrii Zadaianchuk, Davide Allegro, Samuele Papa, Stefano Ghidoni, Efstratios Gavves DreamBench++: A Human-Aligned Benchmark for Personalized Image Generation
Yuang Peng, Yuxin Cui, Haomiao Tang, Zekun Qi, Runpei Dong, Jing Bai, Chunrui Han, Zheng Ge, Xiangyu Zhang, Shu-Tao Xia DreamDistribution: Learning Prompt Distribution for Diverse In-Distribution Generation
Brian Nlong Zhao, Yuhang Xiao, Jiashu Xu, Xinyang Jiang, Yifan Yang, Dongsheng Li, Laurent Itti, Vibhav Vineet, Yunhao Ge DRESSing up LLM: Efficient Stylized Question-Answering via Style Subspace Editing
Xinyu Ma, Yifeng Xu, Yang Lin, Tianlong Wang, Xu Chu, Xin Gao, Junfeng Zhao, Yasha Wang DRoP: Distributionally Robust Data Pruning
Artem M Vysogorets, Kartik Ahuja, Julia Kempe DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?
Liqiang Jing, Zhehui Huang, Xiaoyang Wang, Wenlin Yao, Wenhao Yu, Kaixin Ma, Hongming Zhang, Xinya Du, Dong Yu DUALFormer: Dual Graph Transformer
Jiaming Zhuo, Yuwei Liu, Yintong Lu, Ziyi Ma, Kun Fu, Chuan Wang, Yuanfang Guo, Zhen Wang, Xiaochun Cao, Liang Yang DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads
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Wangbo Zhao, Yizeng Han, Jiasheng Tang, Kai Wang, Yibing Song, Gao Huang, Fan Wang, Yang You Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining
Daouda Sow, Herbert Woisetschläger, Saikiran Bulusu, Shiqiang Wang, Hans Arno Jacobsen, Yingbin Liang Dynamic Low-Rank Sparse Adaptation for Large Language Models
Weizhong Huang, Yuxin Zhang, Xiawu Zheng, Liuyang, Jing Lin, Yiwu Yao, Rongrong Ji Dynamic Negative Guidance of Diffusion Models
Felix Koulischer, Johannes Deleu, Gabriel Raya, Thomas Demeester, Luca Ambrogioni Dynamic Sparse Training Versus Dense Training: The Unexpected Winner in Image Corruption Robustness
Boqian Wu, Qiao Xiao, Shunxin Wang, Nicola Strisciuglio, Mykola Pechenizkiy, Maurice van Keulen, Decebal Constantin Mocanu, Elena Mocanu Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks
Chien-yu Huang, Wei-Chih Chen, Shu-wen Yang, Andy T. Liu, Chen-An Li, Yu-Xiang Lin, Wei-Cheng Tseng, Anuj Diwan, Yi-Jen Shih, Jiatong Shi, William Chen, Chih-Kai Yang, Xuanjun Chen, Chi-Yuan Hsiao, Puyuan Peng, Shih-Heng Wang, Chun-Yi Kuan, Ke-Han Lu, Kai-Wei Chang, Fabian Alejandro Ritter Gutierrez, Huang Kuan-Po, Siddhant Arora, You-Kuan Lin, CHUANG Ming To, Eunjung Yeo, Kalvin Chang, Chung-Ming Chien, Kwanghee Choi, Cheng-Hsiu Hsieh, Yi-Cheng Lin, Chee-En Yu, I-Hsiang Chiu, Heitor Guimarães, Jionghao Han, Tzu-Quan Lin, Tzu-Yuan Lin, Homu Chang, Ting-Wu Chang, Chun Wei Chen, Shou-Jen Chen, Yu-Hua Chen, Hsi-Chun Cheng, Kunal Dhawan, Jia-Lin Fang, Shi-Xin Fang, Kuan Yu Fang Chiang, Chi An Fu, Hsien-Fu Hsiao, Ching Yu Hsu, Shao-Syuan Huang, Lee Chen Wei, Hsi-Che Lin, Hsuan-Hao Lin, Hsuan-Ting Lin, Jian-Ren Lin, Ting-Chun Liu, Li-Chun Lu, Tsung-Min Pai, Ankita Pasad, Shih-Yun Shan Kuan, Suwon Shon, Yuxun Tang, Yun-Shao Tsai, Wei Jui Chiang, Tzu-Chieh Wei, Chengxi Wu, Dien-Ruei Wu, Chao-Han Huck Yang, Chieh-Chi Yang, Jia Qi Yip, Shao-Xiang Yuan, Haibin Wu, Karen Livescu, David Harwath, Shinji Watanabe, Hung-yi Lee Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models
Xingzhuo Guo, Yu Zhang, Baixu Chen, Haoran Xu, Jianmin Wang, Mingsheng Long DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenes
Hengwei Bian, Lingdong Kong, Haozhe Xie, Liang Pan, Yu Qiao, Ziwei Liu DynaPrompt: Dynamic Test-Time Prompt Tuning
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Alexandru Dumitrescu, Dani Korpela, Markus Heinonen, Yogesh Verma, Valerii Iakovlev, Vikas Garg, Harri Lähdesmäki E(n) Equivariant Topological Neural Networks
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Yiwei Li, Sekeun Kim, Zihao Wu, Hanqi Jiang, Yi Pan, Pengfei Jin, Sifan Song, Yucheng Shi, Xiaowei Yu, Tianze Yang, Tianming Liu, Quanzheng Li, Xiang Li EdgeRunner: Auto-Regressive Auto-Encoder for Artistic Mesh Generation
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Ruohong Liu, Yuxin Pan, Linjie Xu, Lei Song, Pengcheng You, Yize Chen, Jiang Bian Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Ivan Butakov, Alexander Semenenko, Alexander Tolmachev, Andrey Gladkov, Marina Munkhoeva, Alexey Frolov Efficient Evolutionary Search over Chemical Space with Large Language Models
Haorui Wang, Marta Skreta, Cher Tian Ser, Wenhao Gao, Lingkai Kong, Felix Strieth-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao Zhu, Yuanqi Du, Alan Aspuru-Guzik, Kirill Neklyudov, Chao Zhang Efficient Imitation Under Misspecification
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Xinyu Lin, Chaoqun Yang, Wenjie Wang, Yongqi Li, Cunxiao Du, Fuli Feng, See-Kiong Ng, Tat-Seng Chua Efficient Learning with Sine-Activated Low-Rank Matrices
Yiping Ji, Hemanth Saratchandran, Cameron Gordon, Zeyu Zhang, Simon Lucey Efficient Low-Bit Quantization with Adaptive Scales for Multi-Task Co-Training
Boyu Liu, Haoyu Huang, Linlin Yang, Yanjing Li, Guodong Guo, Xianbin Cao, Baochang Zhang Efficient Reinforcement Learning with Large Language Model Priors
Xue Yan, Yan Song, Xidong Feng, Mengyue Yang, Haifeng Zhang, Haitham Bou Ammar, Jun Wang Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement
Gaurav Patel, Christopher Michael Sandino, Behrooz Mahasseni, Ellen L. Zippi, Erdrin Azemi, Ali Moin, Juri Minxha Efficient Stagewise Pretraining via Progressive Subnetworks
Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar Efficient Top-M Data Values Identification for Data Selection
Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Bryan Kian Hsiang Low Efficiently Parameterized Neural Metriplectic Systems
Anthony Gruber, Kookjin Lee, Haksoo Lim, Noseong Park, Nathaniel Trask EffoVPR: Effective Foundation Model Utilization for Visual Place Recognition
Issar Tzachor, Boaz Lerner, Matan Levy, Michael Green, Tal Berkovitz Shalev, Gavriel Habib, Dvir Samuel, Noam Korngut Zailer, Or Shimshi, Nir Darshan, Rami Ben-Ari EG4D: Explicit Generation of 4D Object Without Score Distillation
Qi Sun, Zhiyang Guo, Ziyu Wan, Jing Nathan Yan, Shengming Yin, Wengang Zhou, Jing Liao, Houqiang Li EgoExo-Gen: Ego-Centric Video Prediction by Watching Exo-Centric Videos
Jilan Xu, Yifei Huang, Baoqi Pei, Junlin Hou, Qingqiu Li, Guo Chen, Yuejie Zhang, Rui Feng, Weidi Xie Eia: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage
Zeyi Liao, Lingbo Mo, Chejian Xu, Mintong Kang, Jiawei Zhang, Chaowei Xiao, Yuan Tian, Bo Li, Huan Sun ElasticTok: Adaptive Tokenization for Image and Video
Wilson Yan, Volodymyr Mnih, Aleksandra Faust, Matei Zaharia, Pieter Abbeel, Hao Liu ELBOing Stein: Variational Bayes with Stein Mixture Inference
Ola Rønning, Eric Nalisnick, Christophe Ley, Padhraic Smyth, Thomas Hamelryck ELFS: Label-Free Coreset Selection with Proxy Training Dynamics
Haizhong Zheng, Elisa Tsai, Yifu Lu, Jiachen Sun, Brian R. Bartoldson, Bhavya Kailkhura, Atul Prakash Eliciting Human Preferences with Language Models
Belinda Z. Li, Alex Tamkin, Noah Goodman, Jacob Andreas Eliminating Position Bias of Language Models: A Mechanistic Approach
Ziqi Wang, Hanlin Zhang, Xiner Li, Kuan-Hao Huang, Chi Han, Shuiwang Ji, Sham M. Kakade, Hao Peng, Heng Ji Elliptic Loss Regularization
Ali Hasan, Haoming Yang, Yuting Ng, Vahid Tarokh EmbedLLM: Learning Compact Representations of Large Language Models
Richard Zhuang, Tianhao Wu, Zhaojin Wen, Andrew Li, Jiantao Jiao, Kannan Ramchandran EmbodiedSAM: Online Segment Any 3D Thing in Real Time
Xiuwei Xu, Huangxing Chen, Linqing Zhao, Ziwei Wang, Jie Zhou, Jiwen Lu Emergence of a High-Dimensional Abstraction Phase in Language Transformers
Emily Cheng, Diego Doimo, Corentin Kervadec, Iuri Macocco, Lei Yu, Alessandro Laio, Marco Baroni Emergent Orientation Maps —— Mechanisms, Coding Efficiency and Robustness
Haixin Zhong, Haoyu Wang, Wei P Dai, Yuchao Huang, Mingyi Huang, Rubin Wang, Anna Wang Roe, Yuguo Yu EMMA: Empowering Multi-Modal Mamba with Structural and Hierarchical Alignment
Yifei Xing, Xiangyuan Lan, Ruiping Wang, Dongmei Jiang, Wenjun Huang, Zheng Qingfang, Yaowei Wang EMOS: Embodiment-Aware Heterogeneous Multi-Robot Operating System with LLM Agents
Junting Chen, Checheng Yu, Xunzhe Zhou, Tianqi Xu, Yao Mu, Mengkang Hu, Wenqi Shao, Yikai Wang, Guohao Li, Lin Shao Encryption-Friendly LLM Architecture
Donghwan Rho, Taeseong Kim, Minje Park, Jung Woo Kim, Hyunsik Chae, Ernest K. Ryu, Jung Hee Cheon Endless Jailbreaks with Bijection Learning
Brian R.Y. Huang, Maximilian Li, Leonard Tang Endowing Visual Reprogramming with Adversarial Robustness
Shengjie Zhou, Xin Cheng, Haiyang Xu, Ming Yan, Tao Xiang, Feng Liu, Lei Feng Energy-Based Backdoor Defense Against Federated Graph Learning
Guancheng Wan, Zitong Shi, Wenke Huang, Guibin Zhang, Dacheng Tao, Mang Ye Energy-Based Diffusion Language Models for Text Generation
Minkai Xu, Tomas Geffner, Karsten Kreis, Weili Nie, Yilun Xu, Jure Leskovec, Stefano Ermon, Arash Vahdat Enhance Multi-View Classification Through Multi-Scale Alignment and Expanded Boundary
Yuena Lin, Yiyuan Wang, Gengyu Lyu, Yongjian Deng, Haichun Cai, Huibin Lin, Haobo Wang, Zhen Yang Enhancing End-to-End Autonomous Driving with Latent World Model
Yingyan Li, Lue Fan, Jiawei He, Yuqi Wang, Yuntao Chen, Zhaoxiang Zhang, Tieniu Tan Enhancing Language Model Agents Using Diversity of Thoughts
Vijay Lingam, Behrooz Omidvar Tehrani, Sujay Sanghavi, Gaurav Gupta, Sayan Ghosh, Linbo Liu, Jun Huan, Anoop Deoras Enhancing Learning with Label Differential Privacy by Vector Approximation
Puning Zhao, Jiafei Wu, Zhe Liu, Li Shen, Zhikun Zhang, Rongfei Fan, Le Sun, Qingming Li Enhancing Prediction Performance Through Influence Measure
Shuguang Yu, Wenqian Xu, Xinyi Zhou, Xuechun Wang, Hongtu Zhu, Fan Zhou Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems
Yunyang Li, Zaishuo Xia, Lin Huang, Xinran Wei, Samuel Harshe, Han Yang, Erpai Luo, Zun Wang, Jia Zhang, Chang Liu, Bin Shao, Mark Gerstein Ensembles of Low-Rank Expert Adapters
Yinghao Li, Vianne R. Gao, Chao Zhang, MohamadAli Torkamani Ensembling Diffusion Models via Adaptive Feature Aggregation
Cong Wang, Kuan Tian, Yonghang Guan, Fei Shen, Zhiwei Jiang, Qing Gu, Jun Zhang Episodic Novelty Through Temporal Distance
Yuhua Jiang, Qihan Liu, Yiqin Yang, Xiaoteng Ma, Dianyu Zhong, Hao Hu, Jun Yang, Bin Liang, Bo Xu, Chongjie Zhang, Qianchuan Zhao Epistemic Monte Carlo Tree Search
Yaniv Oren, Viliam Vadocz, Matthijs T. J. Spaan, Wendelin Boehmer EqNIO: Subequivariant Neural Inertial Odometry
Royina Karegoudra Jayanth, Yinshuang Xu, Ziyun Wang, Evangelos Chatzipantazis, Kostas Daniilidis, Daniel Gehrig Equivariant Masked Position Prediction for Efficient Molecular Representation
Junyi An, Chao Qu, Yun-Fei Shi, XinHao Liu, Qianwei Tang, Fenglei Cao, Yuan Qi Equivariant Neural Functional Networks for Transformers
Hoang V. Tran, Thieu Vo, An Nguyen The, Tho Tran Huu, Minh-Khoi Nguyen-Nhat, Thanh Tran, Duy-Tung Pham, Tan Minh Nguyen Error-Quantified Conformal Inference for Time Series
Junxi Wu, Dongjian Hu, Yajie Bao, Shu-Tao Xia, Changliang Zou ESE: Espresso Sentence Embeddings
Xianming Li, Zongxi Li, Jing Li, Haoran Xie, Qing Li Et-Seed: Efficient Trajectory-Level Se(3) Equivariant Diffusion Policy
Chenrui Tie, Yue Chen, Ruihai Wu, Boxuan Dong, Zeyi Li, Chongkai Gao, Hao Dong EVA: Geometric Inverse Design for Fast Protein Motif-Scaffolding with Coupled Flow
Yufei Huang, Yunshu Liu, Lirong Wu, Haitao Lin, Cheng Tan, Odin Zhang, Zhangyang Gao, Siyuan Li, Zicheng Liu, Yunfan Liu, Tailin Wu, Stan Z. Li Evaluating Semantic Variation in Text-to-Image Synthesis: A Causal Perspective
Xiangru Zhu, Penglei Sun, Yaoxian Song, Yanghua Xiao, Zhixu Li, Chengyu Wang, Jun Huang, Bei Yang, Xiaoxiao Xu Exact Certification of (Graph) Neural Networks Against Label Poisoning
Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Günnemann, Debarghya Ghoshdastidar Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
Maximilian Muschalik, Fabian Fumagalli, Paolo Frazzetto, Janine Strotherm, Luca Hermes, Alessandro Sperduti, Eyke Hüllermeier, Barbara Hammer ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning
Xiao Yu, Baolin Peng, Vineeth Vajipey, Hao Cheng, Michel Galley, Jianfeng Gao, Zhou Yu Execution-Guided Within-Prompt Search for Programming-by-Example
Gust Verbruggen, Ashish Tiwari, Mukul Singh, Vu Le, Sumit Gulwani Expected Return Symmetries
Darius Muglich, Johannes Forkel, Elise van der Pol, Jakob Nicolaus Foerster Expected Sliced Transport Plans
Xinran Liu, Rocio Diaz Martin, Yikun Bai, Ashkan Shahbazi, Matthew Thorpe, Akram Aldroubi, Soheil Kolouri Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank
Wenhao Zhan, Scott Fujimoto, Zheqing Zhu, Jason D. Lee, Daniel Jiang, Yonathan Efroni Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF
Tengyang Xie, Dylan J Foster, Akshay Krishnamurthy, Corby Rosset, Ahmed Hassan Awadallah, Alexander Rakhlin Explore Theory of Mind: Program-Guided Adversarial Data Generation for Theory of Mind Reasoning
Melanie Sclar, Jane Dwivedi-Yu, Maryam Fazel-Zarandi, Yulia Tsvetkov, Yonatan Bisk, Yejin Choi, Asli Celikyilmaz Exploring a Principled Framework for Deep Subspace Clustering
Xianghan Meng, Zhiyuan Huang, Wei He, Xianbiao Qi, Rong Xiao, Chun-Guang Li Exploring Learning Complexity for Efficient Downstream Dataset Pruning
Wenyu Jiang, Zhenlong Liu, Zejian Xie, Songxin Zhang, Bingyi Jing, Hongxin Wei Exploring the Design Space of Visual Context Representation in Video MLLMs
Yifan Du, Yuqi Huo, Kun Zhou, Zijia Zhao, Haoyu Lu, Han Huang, Xin Zhao, Bingning Wang, Weipeng Chen, Ji-Rong Wen Exposure Bracketing Is All You Need for a High-Quality Image
Zhilu Zhang, Shuohao Zhang, Renlong Wu, Zifei Yan, Wangmeng Zuo Expressivity of Neural Networks with Random Weights and Learned Biases
Ezekiel Williams, Alexandre Payeur, Avery Hee-Woon Ryoo, Thomas Jiralerspong, Matthew G Perich, Luca Mazzucato, Guillaume Lajoie F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI
Xu Zheng, Farhad Shirani, Zhuomin Chen, Chaohao Lin, Wei Cheng, Wenbo Guo, Dongsheng Luo FaceShot: Bring Any Character into Life
Junyao Gao, Yanan Sun, Fei Shen, Xin Jiang, Zhening Xing, Kai Chen, Cairong Zhao Facilitating Multi-Turn Function Calling for LLMs via Compositional Instruction Tuning
Mingyang Chen, Sunhaoze, Tianpeng Li, Fan Yang, Hao Liang, KeerLu, Bin Cui, Wentao Zhang, Zenan Zhou, Weipeng Chen Factor Graph-Based Interpretable Neural Networks
Yicong Li, Kuanjiu Zhou, Shuo Yu, Qiang Zhang, Renqiang Luo, Xiaodong Li, Feng Xia FACTS: A Factored State-Space Framework for World Modelling
Li Nanbo, Firas Laakom, Yucheng Xu, Wenyi Wang, Jürgen Schmidhuber Failures to Find Transferable Image Jailbreaks Between Vision-Language Models
Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristobal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, Tony Tong Wang, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez Fair Clustering in the Sliding Window Model
Vincent Cohen-Addad, Shaofeng H.-C. Jiang, Qiaoyuan Yang, Yubo Zhang, Samson Zhou Fair Submodular Cover
Wenjing Chen, Shuo Xing, Samson Zhou, Victoria G. Crawford FairDen: Fair Density-Based Clustering
Lena Krieger, Anna Beer, Pernille Matthews, Anneka Myrup Thiesson, Ira Assent FaithEval: Can Your Language Model Stay Faithful to Context, Even if "The Moon Is Made of Marshmallows"
Yifei Ming, Senthil Purushwalkam, Shrey Pandit, Zixuan Ke, Xuan-Phi Nguyen, Caiming Xiong, Shafiq Joty Fantastic Copyrighted Beasts and How (Not) to Generate Them
Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson Fantastic Targets for Concept Erasure in Diffusion Models and Where to Find Them
Anh Tuan Bui, Thuy-Trang Vu, Long Tung Vuong, Trung Le, Paul Montague, Tamas Abraham, Junae Kim, Dinh Phung Fast and Accurate Blind Flexible Docking
Zizhuo Zhang, Lijun Wu, Kaiyuan Gao, Jiangchao Yao, Tao Qin, Bo Han Fast Feedforward 3D Gaussian Splatting Compression
Yihang Chen, Qianyi Wu, Mengyao Li, Weiyao Lin, Mehrtash Harandi, Jianfei Cai Fast Training and Sampling of Restricted Boltzmann Machines
Nicolas Bereux, Aurélien Decelle, Cyril Furtlehner, Lorenzo Rosset, Beatriz Seoane Fast Uncovering of Protein Sequence Diversity from Structure
Luca Alessandro Silva, Barthelemy Meynard-Piganeau, Carlo Lucibello, Christoph Feinauer Faster Cascades via Speculative Decoding
Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, Sanjiv Kumar FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality
Zhengyao Lv, Chenyang Si, Junhao Song, Zhenyu Yang, Yu Qiao, Ziwei Liu, Kwan-Yee K. Wong Feature-Based Online Bilateral Trade
Solenne Gaucher, Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Vianney Perchet Federated Domain Generalization with Data-Free On-Server Matching Gradient
Trong Binh Nguyen, Duong Minh Nguyen, Jinsun Park, Viet Quoc Pham, Won-Joo Hwang Federated Few-Shot Class-Incremental Learning
Muhammad Anwar Ma'sum, Mahardhika Pratama, Lin Liu, H Habibullah, Ryszard Kowalczyk Federated Residual Low-Rank Adaptation of Large Language Models
Yunlu Yan, Chun-Mei Feng, Wangmeng Zuo, Rick Siow Mong Goh, Yong Liu, Lei Zhu FedTMOS: Efficient One-Shot Federated Learning with Tsetlin Machine
Shannon How Shi Qi, Jagmohan Chauhan, Geoff V. Merrett, Jonathon Hare Feedback Favors the Generalization of Neural ODEs
Jindou Jia, Zihan Yang, Meng Wang, Kexin Guo, Jianfei Yang, Xiang Yu, Lei Guo Feedback Schrödinger Bridge Matching
Panagiotis Theodoropoulos, Nikolaos Komianos, Vincent Pacelli, Guan-Horng Liu, Evangelos Theodorou Ferret-UI 2: Mastering Universal User Interface Understanding Across Platforms
Zhangheng Li, Keen You, Haotian Zhang, Di Feng, Harsh Agrawal, Xiujun Li, Mohana Prasad Sathya Moorthy, Jeffrey Nichols, Yinfei Yang, Zhe Gan Fewer May Be Better: Enhancing Offline Reinforcement Learning with Reduced Dataset
Yiqin Yang, Quanwei Wang, Chenghao Li, Hao Hu, Chengjie Wu, Yuhua Jiang, Dianyu Zhong, Ziyou Zhang, Qianchuan Zhao, Chongjie Zhang, Bo Xu Filtered Not Mixed: Filtering-Based Online Gating for Mixture of Large Language Models
Raeid Saqur, Anastasis Kratsios, Florian Krach, Yannick Limmer, Blanka Horvath, Frank Rudzicz Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design
Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Avantika Lal, Tommi Jaakkola, Sergey Levine, Aviv Regev, Hanchen, Tommaso Biancalani Fine-Tuning with Reserved Majority for Noise Reduction
Shuyang Jiang, Yusheng Liao, Ya Zhang, Yanfeng Wang, Yu Wang First-Person Fairness in Chatbots
Tyna Eloundou, Alex Beutel, David G. Robinson, Keren Gu, Anna-Luisa Brakman, Pamela Mishkin, Meghan Shah, Johannes Heidecke, Lilian Weng, Adam Tauman Kalai FlashMask: Efficient and Rich Mask Extension of FlashAttention
Guoxia Wang, Jinle Zeng, Xiyuan Xiao, Siming Wu, Jiabin Yang, Lujing Zheng, Zeyu Chen, Jiang Bian, Dianhai Yu, Haifeng Wang FlickerFusion: Intra-Trajectory Domain Generalizing Multi-Agent Reinforcement Learning
Woosung Koh, Wonbeen Oh, Siyeol Kim, Suhin Shin, Hyeongjin Kim, Jaein Jang, Junghyun Lee, Se-Young Yun FLOPS: Forward Learning with OPtimal Sampling
Tao Ren, Zishi Zhang, Jinyang Jiang, Guanghao Li, Zeliang Zhang, Mingqian Feng, Yijie Peng Flow Matching Achieves Almost Minimax Optimal Convergence
Kenji Fukumizu, Taiji Suzuki, Noboru Isobe, Kazusato Oko, Masanori Koyama Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective
Neta Shaul, Itai Gat, Marton Havasi, Daniel Severo, Anuroop Sriram, Peter Holderrieth, Brian Karrer, Yaron Lipman, Ricky T. Q. Chen Flow: Modularized Agentic Workflow Automation
Boye Niu, Yiliao Song, Kai Lian, Yifan Shen, Yu Yao, Kun Zhang, Tongliang Liu FlowDec: A Flow-Based Full-Band General Audio Codec with High Perceptual Quality
Simon Welker, Matthew Le, Ricky T. Q. Chen, Wei-Ning Hsu, Timo Gerkmann, Alexander Richard, Yi-Chiao Wu Fluid: Scaling Autoregressive Text-to-Image Generative Models with Continuous Tokens
Lijie Fan, Tianhong Li, Siyang Qin, Yuanzhen Li, Chen Sun, Michael Rubinstein, Deqing Sun, Kaiming He, Yonglong Tian Following the Human Thread in Social Navigation
Luca Scofano, Alessio Sampieri, Tommaso Campari, Valentino Sacco, Indro Spinelli, Lamberto Ballan, Fabio Galasso ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities
Ezra Karger, Houtan Bastani, Chen Yueh-Han, Zachary Jacobs, Danny Halawi, Fred Zhang, Philip Tetlock Forewarned Is Forearmed: Harnessing LLMs for Data Synthesis via Failure-Induced Exploration
Qintong Li, Jiahui Gao, Sheng Wang, Renjie Pi, Xueliang Zhao, Chuan Wu, Xin Jiang, Zhenguo Li, Lingpeng Kong Forking Paths in Neural Text Generation
Eric J Bigelow, Ari Holtzman, Hidenori Tanaka, Tomer Ullman FormalAlign: Automated Alignment Evaluation for Autoformalization
Jianqiao Lu, Yingjia Wan, Yinya Huang, Jing Xiong, Zhengying Liu, Zhijiang Guo Formation of Representations in Neural Networks
Liu Ziyin, Isaac L. Chuang, Tomer Galanti, Tomaso A Poggio Forte : Finding Outliers with Representation Typicality Estimation
Debargha Ganguly, Warren Richard Morningstar, Andrew Seohwan Yu, Vipin Chaudhary FOSP: Fine-Tuning Offline Safe Policy Through World Models
Chenyang Cao, Yucheng Xin, Silang Wu, Longxiang He, Zichen Yan, Junbo Tan, Xueqian Wang Frame-Voyager: Learning to Query Frames for Video Large Language Models
Sicheng Yu, Chengkai Jin, Huanyu Wang, Zhenghao Chen, Sheng Jin, Zhongrong Zuo, Xu Xiaolei, Zhenbang Sun, Bingni Zhang, Jiawei Wu, Hao Zhang, Qianru Sun Framer: Interactive Frame Interpolation
Wen Wang, Qiuyu Wang, Kecheng Zheng, Hao Ouyang, Zhekai Chen, Biao Gong, Hao Chen, Yujun Shen, Chunhua Shen FreDF: Learning to Forecast in the Frequency Domain
Hao Wang, Lichen Pan, Yuan Shen, Zhichao Chen, Degui Yang, Yifei Yang, Sen Zhang, Xinggao Liu, Haoxuan Li, Dacheng Tao FreeVS: Generative View Synthesis on Free Driving Trajectory
Qitai Wang, Lue Fan, Yuqi Wang, Yuntao Chen, Zhaoxiang Zhang Frequency-Guided Masking for Enhanced Vision Self-Supervised Learning
Amin Karimi Monsefi, Mengxi Zhou, Nastaran Karimi Monsefi, Ser-Nam Lim, Wei-Lun Chao, Rajiv Ramnath FreSh: Frequency Shifting for Accelerated Neural Representation Learning
Adam Kania, Marko Mihajlovic, Sergey Prokudin, Jacek Tabor, Przemysław Spurek From an LLM Swarm to a PDDL-Empowered Hive: Planning Self-Executed Instructions in a Multi-Modal Jungle
Kaustubh Vyas, Damien Graux, Yijun Yang, Sebastien Montella, Chenxin Diao, Wendi Zhou, Pavlos Vougiouklis, Ruofei Lai, Yang Ren, Keshuang Li, Jeff Z. Pan From Commands to Prompts: LLM-Based Semantic File System for AIOS
Zeru Shi, Kai Mei, Mingyu Jin, Yongye Su, Chaoji Zuo, Wenyue Hua, Wujiang Xu, Yujie Ren, Zirui Liu, Mengnan Du, Dong Deng, Yongfeng Zhang From Decoupling to Adaptive Transformation: A Wider Optimization Space for PTQ
Zhaojing Wen, Qiulin Zhang, Yuan Zhang, Rudan Chen, Xichao Yang, Di Xie, Jiang Zhu From Exploration to Mastery: Enabling LLMs to Master Tools via Self-Driven Interactions
Changle Qu, Sunhao Dai, Xiaochi Wei, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Jun Xu, Ji-Rong Wen From GNNs to Trees: Multi-Granular Interpretability for Graph Neural Networks
Jie Yang, Yuwen Wang, Kaixuan Chen, Tongya Zheng, Yihe Zhou, Zhenbang Xiao, Ji Cao, Mingli Song, Shunyu Liu From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
Clémentine Carla Juliette Dominé, Nicolas Anguita, Alexandra Maria Proca, Lukas Braun, Daniel Kunin, Pedro A. M. Mediano, Andrew M Saxe From Models to Microtheories: Distilling a Model's Topical Knowledge for Grounded Question-Answering
Nathaniel Weir, Bhavana Dalvi Mishra, Orion Weller, Oyvind Tafjord, Sam Hornstein, Alexander Sabol, Peter Jansen, Benjamin Van Durme, Peter Clark From Pixels to Tokens: Byte-Pair Encoding on Quantized Visual Modalities
Wanpeng Zhang, Zilong Xie, Yicheng Feng, Yijiang Li, Xingrun Xing, Sipeng Zheng, Zongqing Lu From Tokens to Words: On the Inner Lexicon of LLMs
Guy Kaplan, Matanel Oren, Yuval Reif, Roy Schwartz Fugatto 1: Foundational Generative Audio Transformer Opus 1
Rafael Valle, Rohan Badlani, Zhifeng Kong, Sang-gil Lee, Arushi Goel, Sungwon Kim, Joao Felipe Santos, Shuqi Dai, Siddharth Gururani, Aya Aljafari, Alexander H. Liu, Kevin J. Shih, Ryan Prenger, Wei Ping, Chao-Han Huck Yang, Bryan Catanzaro Fully-Inductive Node Classification on Arbitrary Graphs
Jianan Zhao, Zhaocheng Zhu, Mikhail Galkin, Hesham Mostafa, Michael M. Bronstein, Jian Tang G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model
Jiahui Gao, Renjie Pi, Jipeng Zhang, Jiacheng Ye, Wanjun Zhong, Yufei Wang, Lanqing Hong, Jianhua Han, Hang Xu, Zhenguo Li, Lingpeng Kong GALA: Geometry-Aware Local Adaptive Grids for Detailed 3D Generation
Dingdong Yang, Yizhi Wang, Konrad Schindler, Ali Mahdavi Amiri, Hao Zhang GameArena: Evaluating LLM Reasoning Through Live Computer Games
Lanxiang Hu, Qiyu Li, Anze Xie, Nan Jiang, Ion Stoica, Haojian Jin, Hao Zhang GameGen-X: Interactive Open-World Game Video Generation
Haoxuan Che, Xuanhua He, Quande Liu, Cheng Jin, Hao Chen Gaussian Splatting Lucas-Kanade
Liuyue Xie, Joel Julin, Koichiro Niinuma, Laszlo Attila Jeni GaussianAnything: Interactive Point Cloud Flow Matching for 3D Generation
Yushi Lan, Shangchen Zhou, Zhaoyang Lyu, Fangzhou Hong, Shuai Yang, Bo Dai, Xingang Pan, Chen Change Loy GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-Time Alignment
Yuancheng Xu, Udari Madhushani Sehwag, Alec Koppel, Sicheng Zhu, Bang An, Furong Huang, Sumitra Ganesh GenDataAgent: On-the-Fly Dataset Augmentation with Synthetic Data
Zhiteng Li, Lele Chen, Jerone Andrews, Yunhao Ba, Yulun Zhang, Alice Xiang Generalizable Human Gaussians from Single-View Image
Jinnan Chen, Chen Li, Jianfeng Zhang, Lingting Zhu, Buzhen Huang, Hanlin Chen, Gim Hee Lee Generalizable Motion Planning via Operator Learning
Sharath Matada, Luke Bhan, Yuanyuan Shi, Nikolay Atanasov Generalization and Distributed Learning of GFlowNets
Tiago Silva, Amauri H Souza, Omar Rivasplata, Vikas Garg, Samuel Kaski, Diego Mesquita Generalization V.s. Memorization: Tracing Language Models’ Capabilities Back to Pretraining Data
Xinyi Wang, Antonis Antoniades, Yanai Elazar, Alfonso Amayuelas, Alon Albalak, Kexun Zhang, William Yang Wang Generalized Behavior Learning from Diverse Demonstrations
Varshith Sreeramdass, Rohan R Paleja, Letian Chen, Sanne van Waveren, Matthew Gombolay Generalized Video Moment Retrieval
You Qin, Qilong Wu, Yicong Li, Wei Ji, Li Li, Pengcheng Cai, Lina Wei, Roger Zimmermann Generating CAD Code with Vision-Language Models for 3D Designs
Kamel Alrashedy, Pradyumna Tambwekar, Zulfiqar Haider Zaidi, Megan Langwasser, Wei Xu, Matthew Gombolay Generating Graphs via Spectral Diffusion
Giorgia Minello, Alessandro Bicciato, Luca Rossi, Andrea Torsello, Luca Cosmo Generative Adapter: Contextualizing Language Models in Parameters with a Single Forward Pass
Tong Chen, Hao Fang, Patrick Xia, Xiaodong Liu, Benjamin Van Durme, Luke Zettlemoyer, Jianfeng Gao, Hao Cheng Generative Classifiers Avoid Shortcut Solutions
Alexander Cong Li, Ananya Kumar, Deepak Pathak Generative Flows on Synthetic Pathway for Drug Design
Seonghwan Seo, Minsu Kim, Tony Shen, Martin Ester, Jinkyoo Park, Sungsoo Ahn, Woo Youn Kim Generative Inbetweening: Adapting Image-to-Video Models for Keyframe Interpolation
Xiaojuan Wang, Boyang Zhou, Brian Curless, Ira Kemelmacher-Shlizerman, Aleksander Holynski, Steve Seitz Generative Representational Instruction Tuning
Niklas Muennighoff, Hongjin Su, Liang Wang, Nan Yang, Furu Wei, Tao Yu, Amanpreet Singh, Douwe Kiela Generative Verifiers: Reward Modeling as Next-Token Prediction
Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, Rishabh Agarwal Generator Matching: Generative Modeling with Arbitrary Markov Processes
Peter Holderrieth, Marton Havasi, Jason Yim, Neta Shaul, Itai Gat, Tommi Jaakkola, Brian Karrer, Ricky T. Q. Chen, Yaron Lipman GenEx: Generating an Explorable World
TaiMing Lu, Tianmin Shu, Alan Yuille, Daniel Khashabi, Jieneng Chen GenVP: Generating Visual Puzzles with Contrastive Hierarchical VAEs
Kalliopi Basioti, Pritish Sahu, Tony Qingze Liu, Zihao Xu, Hao Wang, Vladimir Pavlovic GenXD: Generating Any 3D and 4D Scenes
Yuyang Zhao, Chung-Ching Lin, Kevin Lin, Zhiwen Yan, Linjie Li, Zhengyuan Yang, Jianfeng Wang, Gim Hee Lee, Lijuan Wang GeoLoRA: Geometric Integration for Parameter Efficient Fine-Tuning
Steffen Schotthöfer, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco, Jonas Kusch GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-Training
Renqiu Xia, Mingsheng Li, Hancheng Ye, Wenjie Wu, Hongbin Zhou, Jiakang Yuan, Tianshuo Peng, Xinyu Cai, Xiangchao Yan, Bin Wang, Conghui He, Botian Shi, Tao Chen, Junchi Yan, Bo Zhang GeSubNet: Gene Interaction Inference for Disease Subtype Network Generation
Ziwei Yang, Zheng Chen, Xin Liu, Rikuto Kotoge, Peng Chen, Yasuko Matsubara, Yasushi Sakurai, Jimeng Sun Glad: A Streaming Scene Generator for Autonomous Driving
Bin Xie, Yingfei Liu, Tiancai Wang, Jiale Cao, Xiangyu Zhang Global Convergence of Policy Gradient in Average Reward MDPs
Navdeep Kumar, Yashaswini Murthy, Itai Shufaro, Kfir Yehuda Levy, R. Srikant, Shie Mannor GMValuator: Similarity-Based Data Valuation for Generative Models
Jiaxi Yang, Wenlong Deng, Benlin Liu, Yangsibo Huang, James Zou, Xiaoxiao Li Gnothi Seauton: Empowering Faithful Self-Interpretability in Black-Box Transformers
Shaobo Wang, Hongxuan Tang, Mingyang Wang, Hongrui Zhang, Xuyang Liu, Weiya Li, Xuming Hu, Linfeng Zhang GOFA: A Generative One-for-All Model for Joint Graph Language Modeling
Lecheng Kong, Jiarui Feng, Hao Liu, Chengsong Huang, Jiaxin Huang, Yixin Chen, Muhan Zhang GPS: A Probabilistic Distributional Similarity with Gumbel Priors for Set-to-Set Matching
Ziming Zhang, Fangzhou Lin, Haotian Liu, Jose Morales, Haichong Zhang, Kazunori Yamada, Vijaya B Kolachalama, Venkatesh Saligrama GPUDrive: Data-Driven, Multi-Agent Driving Simulation at 1 Million FPS
Saman Kazemkhani, Aarav Pandya, Daphne Cornelisse, Brennan Shacklett, Eugene Vinitsky Gradient Correlation Is a Key Ingredient to Accelerate SGD with Momentum
Julien Hermant, Marien Renaud, Jean-François Aujol, Charles Dossal, Aude Rondepierre Gradient-Free Generation for Hard-Constrained Systems
Chaoran Cheng, Boran Han, Danielle C. Maddix, Abdul Fatir Ansari, Andrew Stuart, Michael W. Mahoney, Bernie Wang GRAIN: Exact Graph Reconstruction from Gradients
Maria Drencheva, Ivo Petrov, Maximilian Baader, Dimitar Iliev Dimitrov, Martin Vechev Gramian Multimodal Representation Learning and Alignment
Giordano Cicchetti, Eleonora Grassucci, Luigi Sigillo, Danilo Comminiello Graph Neural Networks Can (Often) Count Substructures
Paolo Pellizzoni, Till Hendrik Schulz, Karsten Borgwardt Graph Neural Networks Gone Hogwild
Olga Solodova, Nick Richardson, Deniz Oktay, Ryan P Adams Graph Sparsification via Mixture of Graphs
Guibin Zhang, Xiangguo Sun, Yanwei Yue, Chonghe Jiang, Kun Wang, Tianlong Chen, Shirui Pan Graph-Based Document Structure Analysis
Yufan Chen, Ruiping Liu, Junwei Zheng, Di Wen, Kunyu Peng, Jiaming Zhang, Rainer Stiefelhagen Graph-Guided Scene Reconstruction from Images with 3D Gaussian Splatting
Chong Cheng, Gaochao Song, Yiyang Yao, Qinzheng Zhou, Gangjian Zhang, Hao Wang gRNAde: Geometric Deep Learning for 3D RNA Inverse Design
Chaitanya K. Joshi, Arian Rokkum Jamasb, Ramon Viñas Torné, Charles Harris, Simon V Mathis, Alex Morehead, Rishabh Anand, Pietro Lio Grokking at the Edge of Numerical Stability
Lucas Prieto, Melih Barsbey, Pedro A. M. Mediano, Tolga Birdal GROOT-2: Weakly Supervised Multimodal Instruction Following Agents
Shaofei Cai, Bowei Zhang, Zihao Wang, Haowei Lin, Xiaojian Ma, Anji Liu, Yitao Liang Grounding Continuous Representations in Geometry: Equivariant Neural Fields
David Wessels, David M Knigge, Riccardo Valperga, Samuele Papa, Sharvaree Vadgama, Efstratios Gavves, Erik J Bekkers Group Distributionally Robust Dataset Distillation with Risk Minimization
Saeed Vahidian, Mingyu Wang, Jianyang Gu, Vyacheslav Kungurtsev, Wei Jiang, Yiran Chen Group Ligands Docking to Protein Pockets
Jiaqi Guan, Jiahan Li, Xiangxin Zhou, Xingang Peng, Sheng Wang, Yunan Luo, Jian Peng, Jianzhu Ma Growth Inhibitors for Suppressing Inappropriate Image Concepts in Diffusion Models
Die Chen, Zhiwen Li, Mingyuan Fan, Cen Chen, Wenmeng Zhou, Yanhao Wang, Yaliang Li GS-CPR: Efficient Camera Pose Refinement via 3D Gaussian Splatting
Changkun Liu, Shuai Chen, Yash Sanjay Bhalgat, Siyan Hu, Ming Cheng, Zirui Wang, Victor Adrian Prisacariu, Tristan Braud GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models
Seyed Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, Oncel Tuzel, Samy Bengio, Mehrdad Farajtabar GTR: Improving Large 3D Reconstruction Models Through Geometry and Texture Refinement
Peiye Zhuang, Songfang Han, Chaoyang Wang, Aliaksandr Siarohin, Jiaxu Zou, Michael Vasilkovsky, Vladislav Shakhrai, Sergei Korolev, Sergey Tulyakov, Hsin-Ying Lee Guaranteed Generation from Large Language Models
Minbeom Kim, Thibaut Thonet, Jos Rozen, Hwaran Lee, Kyomin Jung, Marc Dymetman GUI-World: A Video Benchmark and Dataset for Multimodal GUI-Oriented Understanding
Dongping Chen, Yue Huang, Siyuan Wu, Jingyu Tang, Huichi Zhou, Qihui Zhang, Zhigang He, Yilin Bai, Chujie Gao, Liuyi Chen, Yiqiang Li, Chenlong Wang, Yue Yu, Tianshuo Zhou, Zhen Li, Yi Gui, Yao Wan, Pan Zhou, Jianfeng Gao, Lichao Sun Gumbel Counterfactual Generation from Language Models
Shauli Ravfogel, Anej Svete, Vésteinn Snæbjarnarson, Ryan Cotterell Gyrogroup Batch Normalization
Ziheng Chen, Yue Song, Xiaojun Wu, Nicu Sebe H4rm3l: A Language for Composable Jailbreak Attack Synthesis
Moussa Koulako Bala Doumbouya, Ananjan Nandi, Gabriel Poesia, Davide Ghilardi, Anna Goldie, Federico Bianchi, Dan Jurafsky, Christopher D Manning Hadamrnn: Binary and Sparse Ternary Orthogonal RNNs
Armand Foucault, Francois Malgouyres, Franck Mamalet Hallo2: Long-Duration and High-Resolution Audio-Driven Portrait Image Animation
Jiahao Cui, Hui Li, Yao Yao, Hao Zhu, Hanlin Shang, Kaihui Cheng, Hang Zhou, Siyu Zhu, Jingdong Wang Halton Scheduler for Masked Generative Image Transformer
Victor Besnier, Mickael Chen, David Hurych, Eduardo Valle, Matthieu Cord HAMSTER: Hierarchical Action Models for Open-World Robot Manipulation
Yi Li, Yuquan Deng, Jesse Zhang, Joel Jang, Marius Memmel, Caelan Reed Garrett, Fabio Ramos, Dieter Fox, Anqi Li, Abhishek Gupta, Ankit Goyal Handling Delay in Real-Time Reinforcement Learning
Ivan Anokhin, Rishav Rishav, Matthew Riemer, Stephen Chung, Irina Rish, Samira Ebrahimi Kahou HARDMath: A Benchmark Dataset for Challenging Problems in Applied Mathematics
Jingxuan Fan, Sarah Martinson, Erik Y. Wang, Kaylie Hausknecht, Jonah Brenner, Danxian Liu, Nianli Peng, Corey Wang, Michael Brenner HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models
Seanie Lee, Haebin Seong, Dong Bok Lee, Minki Kang, Xiaoyin Chen, Dominik Wagner, Yoshua Bengio, Juho Lee, Sung Ju Hwang Harnessing Diversity for Important Data Selection in Pretraining Large Language Models
Chi Zhang, Huaping Zhong, Kuan Zhang, Chengliang Chai, Rui Wang, Xinlin Zhuang, Tianyi Bai, Qiu Jiantao, Lei Cao, Ju Fan, Ye Yuan, Guoren Wang, Conghui He Harnessing Webpage UIs for Text-Rich Visual Understanding
Junpeng Liu, Tianyue Ou, Yifan Song, Yuxiao Qu, Wai Lam, Chenyan Xiong, Wenhu Chen, Graham Neubig, Xiang Yue HART: Efficient Visual Generation with Hybrid Autoregressive Transformer
Haotian Tang, Yecheng Wu, Shang Yang, Enze Xie, Junsong Chen, Junyu Chen, Zhuoyang Zhang, Han Cai, Yao Lu, Song Han Have the VLMs Lost Confidence? a Study of Sycophancy in VLMs
Shuo Li, Tao Ji, Xiaoran Fan, Linsheng Lu, Leyi Yang, Yuming Yang, Zhiheng Xi, Rui Zheng, Yuran Wang, Xh.Zhao, Tao Gui, Qi Zhang, Xuanjing Huang HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models
Hayk Manukyan, Andranik Sargsyan, Barsegh Atanyan, Zhangyang Wang, Shant Navasardyan, Humphrey Shi Heavy-Tailed Diffusion Models
Kushagra Pandey, Jaideep Pathak, Yilun Xu, Stephan Mandt, Michael Pritchard, Arash Vahdat, Morteza Mardani HELM: Hierarchical Encoding for mRNA Language Modeling
Mehdi Yazdani-Jahromi, Mangal Prakash, Tommaso Mansi, Artem Moskalev, Rui Liao HELMET: How to Evaluate Long-Context Models Effectively and Thoroughly
Howard Yen, Tianyu Gao, Minmin Hou, Ke Ding, Daniel Fleischer, Peter Izsak, Moshe Wasserblat, Danqi Chen HelpSteer2-Preference: Complementing Ratings with Preferences
Zhilin Wang, Alexander Bukharin, Olivier Delalleau, Daniel Egert, Gerald Shen, Jiaqi Zeng, Oleksii Kuchaiev, Yi Dong Herald: A Natural Language Annotated Lean 4 Dataset
Guoxiong Gao, Yutong Wang, Jiedong Jiang, Qi Gao, Zihan Qin, Tianyi Xu, Bin Dong HERO: Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuning
Ayano Hiranaka, Shang-Fu Chen, Chieh-Hsin Lai, Dongjun Kim, Naoki Murata, Takashi Shibuya, Wei-Hsiang Liao, Shao-Hua Sun, Yuki Mitsufuji Hessian-Free Online Certified Unlearning
Xinbao Qiao, Meng Zhang, Ming Tang, Ermin Wei Hidden in the Noise: Two-Stage Robust Watermarking for Images
Kasra Arabi, Benjamin Feuer, R. Teal Witter, Chinmay Hegde, Niv Cohen Hierarchical Uncertainty Estimation for Learning-Based Registration in Neuroimaging
Xiaoling Hu, Karthik Gopinath, Peirong Liu, Malte Hoffmann, Koen Van Leemput, Oula Puonti, Juan Eugenio Iglesias Hierarchical World Models as Visual Whole-Body Humanoid Controllers
Nicklas Hansen, S V Jyothir, Vlad Sobal, Yann LeCun, Xiaolong Wang, Hao Su Hierarchically Encapsulated Representation for Protocol Design in Self-Driving Labs
Yu-Zhe Shi, Mingchen Liu, Fanxu Meng, Qiao Xu, Zhangqian Bi, Kun He, Lecheng Ruan, Qining Wang High-Dimension Prototype Is a Better Incremental Object Detection Learner
Yanjie Wang, Liqun Chen, Tianming Zhao, Tao Zhang, Guodong Wang, Luxin Yan, Sheng Zhong, Jiahuan Zhou, Xu Zou High-Precision Dichotomous Image Segmentation via Probing Diffusion Capacity
Qian Yu, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Bo Li, Lihe Zhang, Huchuan Lu High-Quality Joint Image and Video Tokenization with Causal VAE
Dawit Mureja Argaw, Xian Liu, Qinsheng Zhang, Joon Son Chung, Ming-Yu Liu, Fitsum Reda Holistically Evaluating the Environmental Impact of Creating Language Models
Jacob Morrison, Clara Na, Jared Fernandez, Tim Dettmers, Emma Strubell, Jesse Dodge Homomorphism Counts as Structural Encodings for Graph Learning
Linus Bao, Emily Jin, Michael M. Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension
Jiahan Li, Tong Chen, Shitong Luo, Chaoran Cheng, Jiaqi Guan, Ruihan Guo, Sheng Wang, Ge Liu, Jian Peng, Jianzhu Ma How Do Large Language Models Understand Graph Patterns? a Benchmark for Graph Pattern Comprehension
Xinnan Dai, Haohao Qu, Yifei Shen, Bohang Zhang, Qihao Wen, Wenqi Fan, Dongsheng Li, Jiliang Tang, Caihua Shan How Does Critical Batch Size Scale in Pre-Training?
Hanlin Zhang, Depen Morwani, Nikhil Vyas, Jingfeng Wu, Difan Zou, Udaya Ghai, Dean Foster, Sham M. Kakade How Does Vision-Language Adaptation Impact the Safety of Vision Language Models?
Seongyun Lee, Geewook Kim, Jiyeon Kim, Hyunji Lee, Hoyeon Chang, Sue Hyun Park, Minjoon Seo How Efficient Is LLM-Generated Code? a Rigorous & High-Standard Benchmark
Ruizhong Qiu, Weiliang Will Zeng, James Ezick, Christopher Lott, Hanghang Tong How Feature Learning Can Improve Neural Scaling Laws
Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan How New Data Permeates LLM Knowledge and How to Dilute It
Chen Sun, Renat Aksitov, Andrey Zhmoginov, Nolan Andrew Miller, Max Vladymyrov, Ulrich Rueckert, Been Kim, Mark Sandler How to Evaluate Reward Models for RLHF
Evan Frick, Tianle Li, Connor Chen, Wei-Lin Chiang, Anastasios Nikolas Angelopoulos, Jiantao Jiao, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica HQ-Edit: A High-Quality Dataset for Instruction-Based Image Editing
Mude Hui, Siwei Yang, Bingchen Zhao, Yichun Shi, Heng Wang, Peng Wang, Cihang Xie, Yuyin Zhou HQGS: High-Quality Novel View Synthesis with Gaussian Splatting in Degraded Scenes
Xin Lin, Shi Luo, Xiaojun Shan, Xiaoyu Zhou, Chao Ren, Lu Qi, Ming-Hsuan Yang, Nuno Vasconcelos HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting
Nian Ran, Peng Xiao, Yue Wang, Wesley Shi, Jianxin Lin, Qi Meng, Richard Allmendinger HShare: Fast LLM Decoding by Hierarchical Key-Value Sharing
Huaijin Wu, Lianqiang Li, Hantao Huang, Tu Yi, Jihang Zhang, Minghui Yu, Junchi Yan Human Simulacra: Benchmarking the Personification of Large Language Models
Qiujie Xie, Qiming Feng, Tianqi Zhang, Qingqiu Li, Linyi Yang, Yuejie Zhang, Rui Feng, Liang He, Shang Gao, Yue Zhang Human-Aligned Chess with a Bit of Search
Yiming Zhang, Athul Paul Jacob, Vivian Lai, Daniel Fried, Daphne Ippolito Human-Inspired Episodic Memory for Infinite Context LLMs
Zafeirios Fountas, Martin Benfeghoul, Adnan Oomerjee, Fenia Christopoulou, Gerasimos Lampouras, Haitham Bou Ammar, Jun Wang Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors
Tianchun Wang, Yuanzhou Chen, Zichuan Liu, Zhanwen Chen, Haifeng Chen, Xiang Zhang, Wei Cheng Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment
Minh-Quan Le, Gaurav Mittal, Tianjian Meng, A S M Iftekhar, Vishwas Suryanarayanan, Barun Patra, Dimitris Samaras, Mei Chen Hymba: A Hybrid-Head Architecture for Small Language Models
Xin Dong, Yonggan Fu, Shizhe Diao, Wonmin Byeon, Zijia Chen, Ameya Sunil Mahabaleshwarkar, Shih-Yang Liu, Matthijs Van keirsbilck, Min-Hung Chen, Yoshi Suhara, Yingyan Celine Lin, Jan Kautz, Pavlo Molchanov Hyper-Connections
Defa Zhu, Hongzhi Huang, Zihao Huang, Yutao Zeng, Yunyao Mao, Banggu Wu, Qiyang Min, Xun Zhou Hyperbolic Genome Embeddings
Raiyan R. Khan, Philippe Chlenski, Itsik Pe'er HyperDAS: Towards Automating Mechanistic Interpretability with Hypernetworks
Jiuding Sun, Jing Huang, Sidharth Baskaran, Karel D'Oosterlinck, Christopher Potts, Michael Sklar, Atticus Geiger HyPoGen: Optimization-Biased Hypernetworks for Generalizable Policy Generation
Hanxiang Ren, Li Sun, Xulong Wang, Pei Zhou, Zewen Wu, Siyan Dong, Difan Zou, Youyi Zheng, Yanchao Yang I Can Hear You: Selective Robust Training for Deepfake Audio Detection
Zirui Zhang, Wei Hao, Aroon Sankoh, William Lin, Emanuel Mendiola-Ortiz, Junfeng Yang, Chengzhi Mao I-Con: A Unifying Framework for Representation Learning
Shaden Naif Alshammari, John R. Hershey, Axel Feldmann, William T. Freeman, Mark Hamilton I2VControl-Camera: Precise Video Camera Control with Adjustable Motion Strength
Wanquan Feng, Jiawei Liu, Pengqi Tu, Tianhao Qi, Mingzhen Sun, Tianxiang Ma, Songtao Zhao, SiYu Zhou, Qian He ICLR: In-Context Learning of Representations
Core Francisco Park, Andrew Lee, Ekdeep Singh Lubana, Yongyi Yang, Maya Okawa, Kento Nishi, Martin Wattenberg, Hidenori Tanaka IDA-VLM: Towards Movie Understanding via ID-Aware Large Vision-Language Model
Yatai Ji, Shilong Zhang, Jie Wu, Peize Sun, Weifeng Chen, Xuefeng Xiao, Sidi Yang, Yujiu Yang, Ping Luo Identification of Intermittent Temporal Latent Process
Yuke Li, Yujia Zheng, Guangyi Chen, Kun Zhang, Heng Huang Identifying Latent State Transitions in Non-Linear Dynamical Systems
Çağlar Hızlı, Çağatay Yıldız, Matthias Bethge, S. T. John, Pekka Marttinen IgGM: A Generative Model for Functional Antibody and Nanobody Design
Rubo Wang, Fandi Wu, Xingyu Gao, Jiaxiang Wu, Peilin Zhao, Jianhua Yao IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning
Jiawen Qin, Haonan Yuan, Qingyun Sun, Lyujin Xu, Jiaqi Yuan, Pengfeng Huang, Zhaonan Wang, Xingcheng Fu, Hao Peng, Jianxin Li, Philip S. Yu Image Watermarks Are Removable Using Controllable Regeneration from Clean Noise
Yepeng Liu, Yiren Song, Hai Ci, Yu Zhang, Haofan Wang, Mike Zheng Shou, Yuheng Bu Image-Level Memorization Detection via Inversion-Based Inference Perturbation
Yue Jiang, Haokun Lin, Yang Bai, Bo Peng, Zhili Liu, Yueming Lyu, Yong Yang, Xingzheng, Jing Dong ImageFolder: Autoregressive Image Generation with Folded Tokens
Xiang Li, Kai Qiu, Hao Chen, Jason Kuen, Jiuxiang Gu, Bhiksha Raj, Zhe Lin ImDy: Human Inverse Dynamics from Imitated Observations
Xinpeng Liu, Junxuan Liang, Zili Lin, Haowen Hou, Yong-Lu Li, Cewu Lu Implicit In-Context Learning
Zhuowei Li, Zihao Xu, Ligong Han, Yunhe Gao, Song Wen, Di Liu, Hao Wang, Dimitris N. Metaxas Implicit Neural Surface Deformation with Explicit Velocity Fields
Lu Sang, Zehranaz Canfes, Dongliang Cao, Florian Bernard, Daniel Cremers Implicit Search via Discrete Diffusion: A Study on Chess
Jiacheng Ye, Zhenyu Wu, Jiahui Gao, Zhiyong Wu, Xin Jiang, Zhenguo Li, Lingpeng Kong Improved Diffusion-Based Generative Model with Better Adversarial Robustness
Zekun Wang, Mingyang Yi, Shuchen Xue, Zhenguo Li, Ming Liu, Bing Qin, Zhi-Ming Ma Improved Sampling Algorithms for Lévy-Itô Diffusion Models
Vadim Popov, Assel Yermekova, Tasnima Sadekova, Artem Khrapov, Mikhail Sergeevich Kudinov Improved Techniques for Optimization-Based Jailbreaking on Large Language Models
Xiaojun Jia, Tianyu Pang, Chao Du, Yihao Huang, Jindong Gu, Yang Liu, Xiaochun Cao, Min Lin Improved Training Technique for Latent Consistency Models
Quan Dao, Khanh Doan, Di Liu, Trung Le, Dimitris N. Metaxas ImProver: Agent-Based Automated Proof Optimization
Riyaz Ahuja, Jeremy Avigad, Prasad Tetali, Sean Welleck Improving Complex Reasoning with Dynamic Prompt Corruption: A Soft Prompt Optimization Approach
Sinan Fan, Liang Xie, Chen Shen, Ge Teng, Xiaosong Yuan, Xiaofeng Zhang, Chenxi Huang, Wenxiao Wang, Xiaofei He, Jieping Ye Improving Data Efficiency via Curating LLM-Driven Rating Systems
Jinlong Pang, Jiaheng Wei, Ankit Shah, Zhaowei Zhu, Yaxuan Wang, Chen Qian, Yang Liu, Yujia Bao, Wei Wei Improving Instruction-Following in Language Models Through Activation Steering
Alessandro Stolfo, Vidhisha Balachandran, Safoora Yousefi, Eric Horvitz, Besmira Nushi Improving Long-Text Alignment for Text-to-Image Diffusion Models
Luping Liu, Chao Du, Tianyu Pang, Zehan Wang, Chongxuan Li, Dong Xu In Search of Forgotten Domain Generalization
Prasanna Mayilvahanan, Roland S. Zimmermann, Thaddäus Wiedemer, Evgenia Rusak, Attila Juhos, Matthias Bethge, Wieland Brendel In Vivo Cell-Type and Brain Region Classification via Multimodal Contrastive Learning
Han Yu, Hanrui Lyu, YiXun Xu, Charlie Windolf, Eric Kenji Lee, Fan Yang, Andrew M Shelton, Olivier Winter, International Brain Laboratory, Eva L Dyer, Chandramouli Chandrasekaran, Nicholas A. Steinmetz, Liam Paninski, Cole Lincoln Hurwitz In-Context Editing: Learning Knowledge from Self-Induced Distributions
Siyuan Qi, Bangcheng Yang, Kailin Jiang, Xiaobo Wang, Jiaqi Li, Yifan Zhong, Yaodong Yang, Zilong Zheng In-Context Time Series Predictor
Jiecheng Lu, Yan Sun, Shihao Yang INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge
Angelika Romanou, Negar Foroutan, Anna Sotnikova, Sree Harsha Nelaturu, Shivalika Singh, Rishabh Maheshwary, Micol Altomare, Zeming Chen, Mohamed A. Haggag, Snegha A, Alfonso Amayuelas, Azril Hafizi Amirudin, Danylo Boiko, Michael Chang, Jenny Chim, Gal Cohen, Aditya Kumar Dalmia, Abraham Diress, Sharad Duwal, Daniil Dzenhaliou, Daniel Fernando Erazo Florez, Fabian Farestam, Joseph Marvin Imperial, Shayekh Bin Islam, Perttu Isotalo, Maral Jabbarishiviari, Börje F. Karlsson, Eldar Khalilov, Christopher Klamm, Fajri Koto, Dominik Krzemiński, Gabriel Adriano de Melo, Syrielle Montariol, Yiyang Nan, Joel Niklaus, Jekaterina Novikova, Johan Samir Obando Ceron, Debjit Paul, Esther Ploeger, Jebish Purbey, Swati Rajwal, Selvan Sunitha Ravi, Sara Rydell, Roshan Santhosh, Drishti Sharma, Marjana Prifti Skenduli, Arshia Soltani Moakhar, Bardia soltani Moakhar, Ayush Kumar Tarun, Azmine Toushik Wasi, Thenuka Ovin Weerasinghe, Serhan Yilmaz, Mike Zhang, Imanol Schlag, Marzieh Fadaee, Sara Hooker, Antoine Bosselut InCoDe: Interpretable Compressed Descriptions for Image Generation
Armand Comas, Aditya Chattopadhyay, Feliu Formosa, Changyu Liu, Octavia Camps, Rene Vidal INFER: A Neural-Symbolic Model for Extrapolation Reasoning on Temporal Knowledge Graph
Ningyuan Li, Haihong E, Tianyu Yao, Tianyi Hu, Yuhan Li, Haoran Luo, Meina Song, Yifan Zhu Inference Scaling for Long-Context Retrieval Augmented Generation
Zhenrui Yue, Honglei Zhuang, Aijun Bai, Kai Hui, Rolf Jagerman, Hansi Zeng, Zhen Qin, Dong Wang, Xuanhui Wang, Michael Bendersky Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Aviral Kumar, Rishabh Agarwal, Sridhar Thiagarajan, Craig Boutilier, Aleksandra Faust Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models
Negin Raoof, Litu Rout, Giannis Daras, Sujay Sanghavi, Constantine Caramanis, Sanjay Shakkottai, Alex Dimakis Infinite-Resolution Integral Noise Warping for Diffusion Models
Yitong Deng, Winnie Lin, Lingxiao Li, Dmitriy Smirnov, Ryan D Burgert, Ning Yu, Vincent Dedun, Mohammad H. Taghavi Influence Functions for Scalable Data Attribution in Diffusion Models
Bruno Kacper Mlodozeniec, Runa Eschenhagen, Juhan Bae, Alexander Immer, David Krueger, Richard E. Turner Influence-Guided Diffusion for Dataset Distillation
Mingyang Chen, Jiawei Du, Bo Huang, Yi Wang, Xiaobo Zhang, Wei Wang Information Theoretic Text-to-Image Alignment
Chao Wang, Giulio Franzese, Alessandro Finamore, Massimo Gallo, Pietro Michiardi Injective Flows for Star-like Manifolds
Marcello Massimo Negri, Jonathan Aellen, Volker Roth InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation
Gaurav Sahu, Abhay Puri, Juan A. Rodriguez, Amirhossein Abaskohi, Mohammad Chegini, Alexandre Drouin, Perouz Taslakian, Valentina Zantedeschi, Alexandre Lacoste, David Vazquez, Nicolas Chapados, Christopher Pal, Sai Rajeswar, Issam H. Laradji Instance-Dependent Early Stopping
Suqin Yuan, Runqi Lin, Lei Feng, Bo Han, Tongliang Liu InstantSwap: Fast Customized Concept Swapping Across Sharp Shape Differences
Chenyang Zhu, Kai Li, Yue Ma, Longxiang Tang, Chengyu Fang, Chubin Chen, Qifeng Chen, Xiu Li InstaRevive: One-Step Image Enhancement via Dynamic Score Matching
Yixuan Zhu, Haolin Wang, Ao Li, Wenliang Zhao, Yansong Tang, Jingxuan Niu, Lei Chen, Jie Zhou, Jiwen Lu Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy
Tong Wu, Shujian Zhang, Kaiqiang Song, Silei Xu, Sanqiang Zhao, Ravi Agrawal, Sathish Reddy Indurthi, Chong Xiang, Prateek Mittal, Wenxuan Zhou Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows
Xiangxin Zhou, Yi Xiao, Haowei Lin, Xinheng He, Jiaqi Guan, Yang Wang, Qiang Liu, Feng Zhou, Liang Wang, Jianzhu Ma Integrative Decoding: Improving Factuality via Implicit Self-Consistency
Yi Cheng, Xiao Liang, Yeyun Gong, Wen Xiao, Song Wang, Yuji Zhang, Wenjun Hou, Kaishuai Xu, Wenge Liu, Wenjie Li, Jian Jiao, Qi Chen, Peng Cheng, Wayne Xiong Intelligence at the Edge of Chaos
Shiyang Zhang, Aakash Patel, Syed A Rizvi, Nianchen Liu, Sizhuang He, Amin Karbasi, Emanuele Zappala, David van Dijk Intent3D: 3D Object Detection in RGB-D Scans Based on Human Intention
Weitai Kang, Mengxue Qu, Jyoti Kini, Yunchao Wei, Mubarak Shah, Yan Yan Interaction Asymmetry: A General Principle for Learning Composable Abstractions
Jack Brady, Julius von Kügelgen, Sebastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel Interactive Speculative Planning: Enhance Agent Efficiency Through Co-Design of System and User Interface
Wenyue Hua, Mengting Wan, Jagannath Shashank Subramanya Sai Vadrevu, Ryan Nadel, Yongfeng Zhang, Chi Wang Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis
Luofeng Liao, Christian Kroer, Sergei Leonenkov, Okke Schrijvers, Liang Shi, Nicolas Stier Moses, Congshan Zhang Interleaved Scene Graphs for Interleaved Text-and-Image Generation Assessment
Dongping Chen, Ruoxi Chen, Shu Pu, Zhaoyi Liu, Yanru Wu, Caixi Chen, Benlin Liu, Yue Huang, Yao Wan, Pan Zhou, Ranjay Krishna Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence
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Lehan Wang, Haonan Wang, Honglong Yang, Jiaji Mao, Zehong Yang, Jun Shen, Xiaomeng Li Interpretable Causal Representation Learning for Biological Data in the Pathway Space
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Thomas Bush, Stephen Chung, Usman Anwar, Adrià Garriga-Alonso, David Krueger Interpreting Language Reward Models via Contrastive Explanations
Junqi Jiang, Tom Bewley, Saumitra Mishra, Freddy Lecue, Manuela Veloso Intrinsic User-Centric Interpretability Through Global Mixture of Experts
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Qian Long, Ruoyan Li, Minglu Zhao, Tao Gao, Demetri Terzopoulos Inverse Constitutional AI: Compressing Preferences into Principles
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Dominik Straub, Tobias F. Niehues, Jan Peters, Constantin A. Rothkopf Inverse Rendering Using Multi-Bounce Path Tracing and Reservoir Sampling
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Yifan Niu, Ziqi Gao, Tingyang Xu, Yang Liu, Yatao Bian, Yu Rong, Junzhou Huang, Jia Li IPDreamer: Appearance-Controllable 3D Object Generation with Complex Image Prompts
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Hao Zhao, Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion Is Large-Scale Pretraining the Secret to Good Domain Generalization?
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Yuheng Zhang, Dian Yu, Baolin Peng, Linfeng Song, Ye Tian, Mingyue Huo, Nan Jiang, Haitao Mi, Dong Yu IterGen: Iterative Semantic-Aware Structured LLM Generation with Backtracking
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Zhihui Xie, Jiahui Gao, Lei Li, Zhenguo Li, Qi Liu, Lingpeng Kong Jamba: Hybrid Transformer-Mamba Language Models
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Gregor Bachmann, Sotiris Anagnostidis, Albert Pumarola, Markos Georgopoulos, Artsiom Sanakoyeu, Yuming Du, Edgar Schönfeld, Ali Thabet, Jonas K Kohler JudgeBench: A Benchmark for Evaluating LLM-Based Judges
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Yong-Hyun Park, Chieh-Hsin Lai, Satoshi Hayakawa, Yuhta Takida, Yuki Mitsufuji Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge
Jiayi Ye, Yanbo Wang, Yue Huang, Dongping Chen, Qihui Zhang, Nuno Moniz, Tian Gao, Werner Geyer, Chao Huang, Pin-Yu Chen, Nitesh V Chawla, Xiangliang Zhang KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks
Taoran Fang, Tianhong Gao, Chunping Wang, YihaoShang, Wei Chow, Lei Chen, Yang Yang KAN: Kolmogorov–Arnold Networks
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Xi Wang, Taketomo Isazawa, Liana Mikaelyan, James Hensman KGARevion: An AI Agent for Knowledge-Intensive Biomedical QA
Xiaorui Su, Yibo Wang, Shanghua Gao, Xiaolong Liu, Valentina Giunchiglia, Djork-Arné Clevert, Marinka Zitnik KinPFN: Bayesian Approximation of RNA Folding Kinetics Using Prior-Data Fitted Networks
Dominik Scheuer, Frederic Runge, Jörg K.H. Franke, Michael T. Wolfinger, Christoph Flamm, Frank Hutter KiVA: Kid-Inspired Visual Analogies for Testing Large Multimodal Models
Eunice Yiu, Maan Qraitem, Anisa Noor Majhi, Charlie Wong, Yutong Bai, Shiry Ginosar, Alison Gopnik, Kate Saenko KLay: Accelerating Arithmetic Circuits for Neurosymbolic AI
Jaron Maene, Vincent Derkinderen, Pedro Zuidberg Dos Martires Knowing Your Target: Target-Aware Transformer Makes Better Spatio-Temporal Video Grounding
Xin Gu, Yaojie Shen, Chenxi Luo, Tiejian Luo, Yan Huang, Yuewei Lin, Heng Fan, Libo Zhang Knowledge Distillation with Multi-Granularity Mixture of Priors for Image Super-Resolution
Simiao Li, Yun Zhang, Wei Li, Hanting Chen, Wenjia Wang, Bingyi Jing, Shaohui Lin, Jie Hu Knowledge Entropy Decay During Language Model Pretraining Hinders New Knowledge Acquisition
Jiyeon Kim, Hyunji Lee, Hyowon Cho, Joel Jang, Hyeonbin Hwang, Seungpil Won, Youbin Ahn, Dohaeng Lee, Minjoon Seo Knowledge Graph Finetuning Enhances Knowledge Manipulation in Large Language Models
Hanzhu Chen, Xu Shen, Jie Wang, Zehao Wang, Qitan Lv, Junjie He, Rong Wu, Feng Wu, Jieping Ye KOR-Bench: Benchmarking Language Models on Knowledge-Orthogonal Reasoning Tasks
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Guneet S. Dhillon, Xingjian Shi, Yee Whye Teh, Alex Smola LaMP: Language-Motion Pretraining for Motion Generation, Retrieval, and Captioning
Zhe Li, Weihao Yuan, Yisheng He, Lingteng Qiu, Shenhao Zhu, Xiaodong Gu, Weichao Shen, Yuan Dong, Zilong Dong, Laurence Tianruo Yang LaMPlace: Learning to Optimize Cross-Stage Metrics in Macro Placement
Zijie Geng, Jie Wang, Ziyan Liu, Siyuan Xu, Zhentao Tang, Shixiong Kai, Mingxuan Yuan, Jianye Hao, Feng Wu Language Agents Meet Causality -- Bridging LLMs and Causal World Models
John Gkountouras, Matthias Lindemann, Phillip Lippe, Efstratios Gavves, Ivan Titov Language Guided Skill Discovery
Seungeun Rho, Laura Smith, Tianyu Li, Sergey Levine, Xue Bin Peng, Sehoon Ha Language Model Alignment in Multilingual Trolley Problems
Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, Sydney Levine, Jiarui Liu, Fernando Gonzalez Adauto, Francesco Ortu, András Strausz, Mrinmaya Sachan, Rada Mihalcea, Yejin Choi, Bernhard Schölkopf Language Models Are Advanced Anonymizers
Robin Staab, Mark Vero, Mislav Balunovic, Martin Vechev Language Models Are Implicitly Continuous
Samuele Marro, Davide Evangelista, X. Angelo Huang, Emanuele La Malfa, Michele Lombardi, Michael J. Wooldridge Language Models Learn to Mislead Humans via RLHF
Jiaxin Wen, Ruiqi Zhong, Akbir Khan, Ethan Perez, Jacob Steinhardt, Minlie Huang, Samuel R. Bowman, He He, Shi Feng Language Models Scale Reliably with Over-Training and on Downstream Tasks
Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Luca Soldaini, Jenia Jitsev, Alex Dimakis, Gabriel Ilharco, Pang Wei Koh, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, Ludwig Schmidt Language-Image Models with 3D Understanding
Jang Hyun Cho, Boris Ivanovic, Yulong Cao, Edward Schmerling, Yue Wang, Xinshuo Weng, Boyi Li, Yurong You, Philipp Kraehenbuehl, Yan Wang, Marco Pavone LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding
Doohyuk Jang, Sihwan Park, June Yong Yang, Yeonsung Jung, Jihun Yun, Souvik Kundu, Sung-Yub Kim, Eunho Yang Laplace Sample Information: Data Informativeness Through a Bayesian Lens
Johannes Kaiser, Kristian Schwethelm, Daniel Rueckert, Georgios Kaissis Large (Vision) Language Models Are Unsupervised In-Context Learners
Artyom Gadetsky, Andrei Atanov, Yulun Jiang, Zhitong Gao, Ghazal Hosseini Mighan, Amir Zamir, Maria Brbic Large Language Models Are Interpretable Learners
Ruochen Wang, Si Si, Felix Yu, Dorothea Wiesmann Rothuizen, Cho-Jui Hsieh, Inderjit S Dhillon Large Language Models Assume People Are More Rational than We Really Are
Ryan Liu, Jiayi Geng, Joshua Peterson, Ilia Sucholutsky, Thomas L. Griffiths Large Language Models Can Become Strong Self-Detoxifiers
Ching-Yun Ko, Pin-Yu Chen, Payel Das, Youssef Mroueh, Soham Dan, Georgios Kollias, Subhajit Chaudhury, Tejaswini Pedapati, Luca Daniel Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluation
Chengwen Qi, Ren Ma, Bowen Li, He Du, Binyuan Hui, Jinwang Wu, Yuanjun Laili, Conghui He Large Language Models Often Say One Thing and Do Another
Ruoxi Xu, Hongyu Lin, Xianpei Han, Jia Zheng, Weixiang Zhou, Le Sun, Yingfei Sun Large Scale Knowledge Washing
Yu Wang, Ruihan Wu, Zexue He, Xiusi Chen, Julian McAuley Large-Scale and Fine-Grained Vision-Language Pre-Training for Enhanced CT Image Understanding
Zhongyi Shui, Jianpeng Zhang, Weiwei Cao, Sinuo Wang, Ruizhe Guo, Le Lu, Lin Yang, Xianghua Ye, Tingbo Liang, Qi Zhang, Ling Zhang Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games
Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng Latent Action Pretraining from Videos
Seonghyeon Ye, Joel Jang, Byeongguk Jeon, Se June Joo, Jianwei Yang, Baolin Peng, Ajay Mandlekar, Reuben Tan, Yu-Wei Chao, Bill Yuchen Lin, Lars Liden, Kimin Lee, Jianfeng Gao, Luke Zettlemoyer, Dieter Fox, Minjoon Seo Latent Bayesian Optimization via Autoregressive Normalizing Flows
Seunghun Lee, Jinyoung Park, Jaewon Chu, Minseo Yoon, Hyunwoo J. Kim Law of the Weakest Link: Cross Capabilities of Large Language Models
Ming Zhong, Aston Zhang, Xuewei Wang, Rui Hou, Wenhan Xiong, Chenguang Zhu, Zhengxing Chen, Liang Tan, Chloe Bi, Mike Lewis, Sravya Popuri, Sharan Narang, Melanie Kambadur, Dhruv Mahajan, Sergey Edunov, Jiawei Han, Laurens van der Maaten Lawma: The Power of Specialization for Legal Annotation
Ricardo Dominguez-Olmedo, Vedant Nanda, Rediet Abebe, Stefan Bechtold, Christoph Engel, Jens Frankenreiter, Krishna P. Gummadi, Moritz Hardt, Michael Livermore Layer Swapping for Zero-Shot Cross-Lingual Transfer in Large Language Models
Lucas Bandarkar, Benjamin Muller, Pritish Yuvraj, Rui Hou, Nayan Singhal, Hongjiang Lv, Bing Liu LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation
Mufei Li, Viraj Shitole, Eli Chien, Changhai Man, Zhaodong Wang, Srinivas, Ying Zhang, Tushar Krishna, Pan Li Layerwise Recurrent Router for Mixture-of-Experts
Zihan Qiu, Zeyu Huang, Shuang Cheng, Yizhi Zhou, Zili Wang, Ivan Titov, Jie Fu LeanAgent: Lifelong Learning for Formal Theorem Proving
Adarsh Kumarappan, Mo Tiwari, Peiyang Song, Robert Joseph George, Chaowei Xiao, Anima Anandkumar Learn Your Reference Model for Real Good Alignment
Alexey Gorbatovski, Boris Shaposhnikov, Alexey Malakhov, Nikita Surnachev, Yaroslav Aksenov, Ian Maksimov, Nikita Balagansky, Daniil Gavrilov Learning 3D Perception from Others' Predictions
Jinsu Yoo, Zhenyang Feng, Tai-Yu Pan, Yihong Sun, Cheng Perng Phoo, Xiangyu Chen, Mark Campbell, Kilian Q Weinberger, Bharath Hariharan, Wei-Lun Chao Learning a Neural Solver for Parametric PDEs to Enhance Physics-Informed Methods
Lise Le Boudec, Emmanuel de Bezenac, Louis Serrano, Ramon Daniel Regueiro-Espino, Yuan Yin, Patrick Gallinari Learning Causal Alignment for Reliable Disease Diagnosis
Mingzhou Liu, Ching-Wen Lee, Xinwei Sun, Xueqing Yu, Yu Qiao, Yizhou Wang Learning Chaos in a Linear Way
Xiaoyuan Cheng, Yi He, Yiming Yang, Xiao Xue, Sibo Cheng, Daniel Giles, Xiaohang Tang, Yukun Hu Learning Color Equivariant Representations
Yulong Yang, Felix O'Mahony, Christine Allen-Blanchette Learning Continually by Spectral Regularization
Alex Lewandowski, Michał Bortkiewicz, Saurabh Kumar, András György, Dale Schuurmans, Mateusz Ostaszewski, Marlos C. Machado Learning Diagrams: A Graphical Language for Compositional Training Regimes
Mason Lary, Richard Samuelson, Alexander Wilentz, Alina Zare, Matthew Klawonn, James Fairbanks Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning
Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain Learning Dynamics of Deep Matrix Factorization Beyond the Edge of Stability
Avrajit Ghosh, Soo Min Kwon, Rongrong Wang, Saiprasad Ravishankar, Qing Qu Learning Efficient Positional Encodings with Graph Neural Networks
Charilaos Kanatsoulis, Evelyn Choi, Stefanie Jegelka, Jure Leskovec, Alejandro Ribeiro Learning Evolving Tools for Large Language Models
Guoxin Chen, Zhong Zhang, Xin Cong, Fangda Guo, Yesai Wu, Yankai Lin, Wenzheng Feng, Yasheng Wang Learning from Negative Feedback, or Positive Feedback or Both
Abbas Abdolmaleki, Bilal Piot, Bobak Shahriari, Jost Tobias Springenberg, Tim Hertweck, Michael Bloesch, Rishabh Joshi, Thomas Lampe, Junhyuk Oh, Nicolas Heess, Jonas Buchli, Martin Riedmiller Learning from Weak Labelers as Constraints
Vishwajeet Agrawal, Rattana Pukdee, Maria Florina Balcan, Pradeep Kumar Ravikumar Learning Gain mAP for Inverse Tone Mapping
Yinuo Liao, Yuanshen Guan, Ruikang Xu, Jiacheng Li, Shida Sun, Zhiwei Xiong Learning General-Purpose Biomedical Volume Representations Using Randomized Synthesis
Neel Dey, Benjamin Billot, Hallee E. Wong, Clinton Wang, Mengwei Ren, Ellen Grant, Adrian V Dalca, Polina Golland Learning Graph Invariance by Harnessing Spuriosity
Tianjun Yao, Yongqiang Chen, Kai Hu, Tongliang Liu, Kun Zhang, Zhiqiang Shen Learning Graph Quantized Tokenizers
Limei Wang, Kaveh Hassani, Si Zhang, Dongqi Fu, Baichuan Yuan, Weilin Cong, Zhigang Hua, Hao Wu, Ning Yao, Bo Long Learning High-Degree Parities: The Crucial Role of the Initialization
Emmanuel Abbe, Elisabetta Cornacchia, Jan Hązła, Donald Kougang-Yombi Learning Interleaved Image-Text Comprehension in Vision-Language Large Models
Chenyu Zhou, Mengdan Zhang, Peixian Chen, Chaoyou Fu, Yunhang Shen, Xiawu Zheng, Xing Sun, Rongrong Ji Learning LLM-as-a-Judge for Preference Alignment
Ziyi Ye, Xiangsheng Li, Qiuchi Li, Qingyao Ai, Yujia Zhou, Wei Shen, Dong Yan, Yiqun Liu Learning Local Equivariant Representations for Quantum Operators
Zhanghao Zhouyin, Zixi Gan, Shishir Kumar Pandey, Linfeng Zhang, Qiangqiang Gu Learning Mirror Maps in Policy Mirror Descent
Carlo Alfano, Sebastian Rene Towers, Silvia Sapora, Chris Lu, Patrick Rebeschini Learning Molecular Representation in a Cell
Gang Liu, Srijit Seal, John Arevalo, Zhenwen Liang, Anne E Carpenter, Meng Jiang, Shantanu Singh Learning Randomized Algorithms with Transformers
Johannes von Oswald, Seijin Kobayashi, Yassir Akram, Angelika Steger Learning Spatial-Semantic Features for Robust Video Object Segmentation
Xin Li, Deshui Miao, Zhenyu He, Yaowei Wang, Huchuan Lu, Ming-Hsuan Yang Learning System Dynamics Without Forgetting
Xikun Zhang, Dongjin Song, Yushan Jiang, Yixin Chen, Dacheng Tao Learning the Complexity of Weakly Noisy Quantum States
Yusen Wu, Bujiao Wu, Yanqi Song, Xiao Yuan, Jingbo Wang Learning to Adapt Frozen CLIP for Few-Shot Test-Time Domain Adaptation
Zhixiang Chi, Li Gu, Huan Liu, Ziqiang Wang, Yanan Wu, Yang Wang, Konstantinos N Plataniotis Learning to Contextualize Web Pages for Enhanced Decision Making by LLM Agents
Dongjun Lee, Juyong Lee, Kyuyoung Kim, Jihoon Tack, Jinwoo Shin, Yee Whye Teh, Kimin Lee Learning to Discretize Denoising Diffusion ODEs
Vinh Tong, Dung Trung Hoang, Anji Liu, Guy Van den Broeck, Mathias Niepert Learning to Engineer Protein Flexibility
Petr Kouba, Joan Planas-Iglesias, Jiri Damborsky, Jiri Sedlar, Stanislav Mazurenko, Josef Sivic Learning to Help in Multi-Class Settings
Yu Wu, Yansong Li, Zeyu Dong, Nitya Sathyavageeswaran, Anand D. Sarwate Learning to Solve Differential Equation Constrained Optimization Problems
Vincenzo Di Vito Francesco, Mostafa Mohammadian, Kyri Baker, Ferdinando Fioretto Learning to Steer Markovian Agents Under Model Uncertainty
Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich H. Nax, Niao He Learning Under Temporal Label Noise
Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen Learning View-Invariant World Models for Visual Robotic Manipulation
Jing-Cheng Pang, Nan Tang, Kaiyuan Li, Yuting Tang, Xin-Qiang Cai, Zhen-Yu Zhang, Gang Niu, Masashi Sugiyama, Yang Yu Learning-Augmented Frequent Directions
Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu Learning-Augmented Search Data Structures
Chunkai Fu, Brandon G. Nguyen, Jung Hoon Seo, Ryan S. Zesch, Samson Zhou LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion Models
Hantao Zhang, Yuhe Liu, Jiancheng Yang, Shouhong Wan, Xinyuan Wang, Wei Peng, Pascal Fua Let the Code LLM Edit Itself When You Edit the Code
Zhenyu He, Jun Zhang, Shengjie Luo, Jingjing Xu, Zhi Zhang, Di He Leveraging Driver Field-of-View for Multimodal Ego-Trajectory Prediction
M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel, Nikola Popovic, Christian Vater, Otmar Hilliges, Luc Van Gool, Xi Wang Lie Algebra Canonicalization: Equivariant Neural Operators Under Arbitrary Lie Groups
Zakhar Shumaylov, Peter Zaika, James Rowbottom, Ferdia Sherry, Melanie Weber, Carola-Bibiane Schönlieb Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space
Mohamed Amine Ketata, Nicholas Gao, Johanna Sommer, Tom Wollschläger, Stephan Günnemann Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models
Dvir Samuel, Barak Meiri, Haggai Maron, Yoad Tewel, Nir Darshan, Shai Avidan, Gal Chechik, Rami Ben-Ari Lightweight Neural App Control
Filippos Christianos, Georgios Papoudakis, Thomas Coste, Jianye Hao, Jun Wang, Kun Shao Lightweight Predictive 3D Gaussian Splats
Junli Cao, Vidit Goel, Chaoyang Wang, Anil Kag, Ju Hu, Sergei Korolev, Chenfanfu Jiang, Sergey Tulyakov, Jian Ren Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Shuaiqi Wang, Matthew B. Blaschko, Sergey Yekhanin, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang Linear Combinations of Latents in Generative Models: Subspaces and Beyond
Erik Bodin, Alexandru I. Stere, Dragos D Margineantu, Carl Henrik Ek, Henry Moss Linear Partial Gromov-Wasserstein Embedding
Yikun Bai, Abihith Kothapalli, Hengrong Du, Rocio Diaz Martin, Soheil Kolouri Linear Spherical Sliced Optimal Transport: A Fast Metric for Comparing Spherical Data
Xinran Liu, Yikun Bai, Rocio Diaz Martin, Kaiwen Shi, Ashkan Shahbazi, Bennett Allan Landman, Catie Chang, Soheil Kolouri Linear Transformer Topological Masking with Graph Random Features
Isaac Reid, Kumar Avinava Dubey, Deepali Jain, William F Whitney, Amr Ahmed, Joshua Ainslie, Alex Bewley, Mithun George Jacob, Aranyak Mehta, David Rendleman, Connor Schenck, Richard E. Turner, René Wagner, Adrian Weller, Krzysztof Marcin Choromanski Lines of Thought in Large Language Models
Raphaël Sarfati, Toni J.B. Liu, Nicolas Boulle, Christopher Earls LiNeS: Post-Training Layer Scaling Prevents Forgetting and Enhances Model Merging
Ke Wang, Nikolaos Dimitriadis, Alessandro Favero, Guillermo Ortiz-Jimenez, François Fleuret, Pascal Frossard LiveBench: A Challenging, Contamination-Limited LLM Benchmark
Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Sreemanti Dey, Shubh-Agrawal, Sandeep Singh Sandha, Siddartha Venkat Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
Naman Jain, King Han, Alex Gu, Wen-Ding Li, Fanjia Yan, Tianjun Zhang, Sida Wang, Armando Solar-Lezama, Koushik Sen, Ion Stoica LiveXiv - A Multi-Modal Live Benchmark Based on arXiv Papers Content
Nimrod Shabtay, Felipe Maia Polo, Sivan Doveh, Wei Lin, Muhammad Jehanzeb Mirza, Leshem Choshen, Mikhail Yurochkin, Yuekai Sun, Assaf Arbelle, Leonid Karlinsky, Raja Giryes Llama-Omni: Seamless Speech Interaction with Large Language Models
Qingkai Fang, Shoutao Guo, Yan Zhou, Zhengrui Ma, Shaolei Zhang, Yang Feng LLaMaFlex: Many-in-One LLMs via Generalized Pruning and Weight Sharing
Ruisi Cai, Saurav Muralidharan, Hongxu Yin, Zhangyang Wang, Jan Kautz, Pavlo Molchanov LLaRA: Supercharging Robot Learning Data for Vision-Language Policy
Xiang Li, Cristina Mata, Jongwoo Park, Kumara Kahatapitiya, Yoo Sung Jang, Jinghuan Shang, Kanchana Ranasinghe, Ryan D Burgert, Mu Cai, Yong Jae Lee, Michael S Ryoo LLaVA-Interleave: Tackling Multi-Image, Video, and 3D in Large Multimodal Models
Feng Li, Renrui Zhang, Hao Zhang, Yuanhan Zhang, Bo Li, Wei Li, Zejun Ma, Chunyuan Li LLaVA-MoD: Making LLaVA Tiny via MoE-Knowledge Distillation
Fangxun Shu, Yue Liao, Lei Zhang, Le Zhuo, Chenning Xu, Guanghao Zhang, Haonan Shi, Long Chan, TaoZhong, Zhelun Yu, Wanggui He, Siming Fu, Haoyuan Li, Si Liu, Hongsheng Li, Hao Jiang LLM Unlearning via Loss Adjustment with Only Forget Data
Yaxuan Wang, Jiaheng Wei, Chris Yuhao Liu, Jinlong Pang, Quan Liu, Ankit Shah, Yujia Bao, Yang Liu, Wei Wei LLM-SR: Scientific Equation Discovery via Programming with Large Language Models
Parshin Shojaee, Kazem Meidani, Shashank Gupta, Amir Barati Farimani, Chandan K. Reddy LLMs Can Plan Only if We Tell Them
Bilgehan Sel, Ruoxi Jia, Ming Jin LLMs Know More than They Show: On the Intrinsic Representation of LLM Hallucinations
Hadas Orgad, Michael Toker, Zorik Gekhman, Roi Reichart, Idan Szpektor, Hadas Kotek, Yonatan Belinkov LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning
Zhekai Du, Yinjie Min, Jingjing Li, Ke Lu, Changliang Zou, Liuhua Peng, Tingjin Chu, Mingming Gong Locality Alignment Improves Vision-Language Models
Ian Connick Covert, Tony Sun, James Zou, Tatsunori Hashimoto Locality Sensitive Avatars from Video
Chunjin Song, Zhijie Wu, Shih-Yang Su, Bastian Wandt, Leonid Sigal, Helge Rhodin Logical Consistency of Large Language Models in Fact-Checking
Bishwamittra Ghosh, Sarah Hasan, Naheed Anjum Arafat, Arijit Khan LOKI: A Comprehensive Synthetic Data Detection Benchmark Using Large Multimodal Models
Junyan Ye, Baichuan Zhou, Zilong Huang, Junan Zhang, Tianyi Bai, Hengrui Kang, Jun He, Honglin Lin, Zihao Wang, Tong Wu, Zhizheng Wu, Yiping Chen, Dahua Lin, Conghui He, Weijia Li LoLCATs: On Low-Rank Linearizing of Large Language Models
Michael Zhang, Simran Arora, Rahul Chalamala, Benjamin Frederick Spector, Alan Wu, Krithik Ramesh, Aaryan Singhal, Christopher Re Long Context Compression with Activation Beacon
Peitian Zhang, Zheng Liu, Shitao Xiao, Ninglu Shao, Qiwei Ye, Zhicheng Dou Long-Context Linear System Identification
Oğuz Kaan Yüksel, Mathieu Even, Nicolas Flammarion Long-Sequence Recommendation Models Need Decoupled Embeddings
Ningya Feng, Junwei Pan, Jialong Wu, Baixu Chen, Ximei Wang, QianLi, Xian Hu, Jie Jiang, Mingsheng Long Long-Short Decision Transformer: Bridging Global and Local Dependencies for Generalized Decision-Making
Jincheng Wang, Penny Karanasou, Pengyuan Wei, Elia Gatti, Diego Martinez Plasencia, Dimitrios Kanoulas Longhorn: State Space Models Are Amortized Online Learners
Bo Liu, Rui Wang, Lemeng Wu, Yihao Feng, Peter Stone, Qiang Liu LongMamba: Enhancing Mamba's Long-Context Capabilities via Training-Free Receptive Field Enlargement
Zhifan Ye, Kejing Xia, Yonggan Fu, Xin Dong, Jihoon Hong, Xiangchi Yuan, Shizhe Diao, Jan Kautz, Pavlo Molchanov, Yingyan Celine Lin LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Yukang Chen, Fuzhao Xue, Dacheng Li, Qinghao Hu, Ligeng Zhu, Xiuyu Li, Yunhao Fang, Haotian Tang, Shang Yang, Zhijian Liu, Yihui He, Hongxu Yin, Pavlo Molchanov, Jan Kautz, Linxi Fan, Yuke Zhu, Yao Lu, Song Han LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs
Yushi Bai, Jiajie Zhang, Xin Lv, Linzhi Zheng, Siqi Zhu, Lei Hou, Yuxiao Dong, Jie Tang, Juanzi Li Looking Backward: Streaming Video-to-Video Translation with Feature Banks
Feng Liang, Akio Kodaira, Chenfeng Xu, Masayoshi Tomizuka, Kurt Keutzer, Diana Marculescu Looking Inward: Language Models Can Learn About Themselves by Introspection
Felix Jedidja Binder, James Chua, Tomek Korbak, Henry Sleight, John Hughes, Robert Long, Ethan Perez, Miles Turpin, Owain Evans Looped Transformers for Length Generalization
Ying Fan, Yilun Du, Kannan Ramchandran, Kangwook Lee Loopy: Taming Audio-Driven Portrait Avatar with Long-Term Motion Dependency
Jianwen Jiang, Chao Liang, Jiaqi Yang, Gaojie Lin, Tianyun Zhong, Yanbo Zheng LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation
Can Jin, Ying Li, Mingyu Zhao, Shiyu Zhao, Zhenting Wang, Xiaoxiao He, Ligong Han, Tong Che, Dimitris N. Metaxas LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization
Jui-Nan Yen, Si Si, Zhao Meng, Felix Yu, Sai Surya Duvvuri, Inderjit S Dhillon, Cho-Jui Hsieh, Sanjiv Kumar LoRA-Pro: Are Low-Rank Adapters Properly Optimized?
Zhengbo Wang, Jian Liang, Ran He, Zilei Wang, Tieniu Tan LoRA3D: Low-Rank Self-Calibration of 3D Geometric Foundation Models
Ziqi Lu, Heng Yang, Danfei Xu, Boyi Li, Boris Ivanovic, Marco Pavone, Yue Wang Lotus: Diffusion-Based Visual Foundation Model for High-Quality Dense Prediction
Jing He, Haodong Li, Wei Yin, Yixun Liang, Leheng Li, Kaiqiang Zhou, Hongbo Zhang, Bingbing Liu, Ying-Cong Chen LucidPPN: Unambiguous Prototypical Parts Network for User-Centric Interpretable Computer Vision
Mateusz Pach, Koryna Lewandowska, Jacek Tabor, Bartosz Michał Zieliński, Dawid Damian Rymarczyk Lumina-T2X: Scalable Flow-Based Large Diffusion Transformer for Flexible Resolution Generation
Peng Gao, Le Zhuo, Dongyang Liu, Ruoyi Du, Xu Luo, Longtian Qiu, Yuhang Zhang, Rongjie Huang, Shijie Geng, Renrui Zhang, Junlin Xie, Wenqi Shao, Zhengkai Jiang, Tianshuo Yang, Weicai Ye, Tong He, Jingwen He, Junjun He, Yu Qiao, Hongsheng Li LVSM: A Large View Synthesis Model with Minimal 3D Inductive Bias
Haian Jin, Hanwen Jiang, Hao Tan, Kai Zhang, Sai Bi, Tianyuan Zhang, Fujun Luan, Noah Snavely, Zexiang Xu Machine Unlearning Fails to Remove Data Poisoning Attacks
Martin Pawelczyk, Jimmy Z. Di, Yiwei Lu, Gautam Kamath, Ayush Sekhari, Seth Neel Machine Unlearning via Simulated Oracle Matching
Kristian Georgiev, Roy Rinberg, Sung Min Park, Shivam Garg, Andrew Ilyas, Aleksander Madry, Seth Neel MACPO: Weak-to-Strong Alignment via Multi-Agent Contrastive Preference Optimization
Yougang Lyu, Lingyong Yan, Zihan Wang, Dawei Yin, Pengjie Ren, Maarten de Rijke, Zhaochun Ren MAD-TD: Model-Augmented Data Stabilizes High Update Ratio RL
Claas A Voelcker, Marcel Hussing, Eric Eaton, Amir-massoud Farahmand, Igor Gilitschenski MAESTRO: Masked Encoding Set Transformer with Self-Distillation
Matthew Eric Lee, Jaesik Kim, Matei Ionita, Jonghyun Lee, Michelle L. McKeague, Yonghyun Nam, Irene Khavin, Yidi Huang, Victoria Fang, Sokratis Apostolidis, Divij Mathew, Shwetank, Ajinkya Pattekar, Zahabia Rangwala, Amit Bar-Or, Benjamin A Fensterheim, Benjamin A. Abramoff, Rennie L. Rhee, Damian Maseda, Allison R Greenplate, John Wherry, Dokyoon Kim MaestroMotif: Skill Design from Artificial Intelligence Feedback
Martin Klissarov, Mikael Henaff, Roberta Raileanu, Shagun Sodhani, Pascal Vincent, Amy Zhang, Pierre-Luc Bacon, Doina Precup, Marlos C. Machado, Pierluca D'Oro MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context Generation with Speculative Decoding
Ranajoy Sadhukhan, Jian Chen, Zhuoming Chen, Vashisth Tiwari, Ruihang Lai, Jinyuan Shi, Ian En-Hsu Yen, Avner May, Tianqi Chen, Beidi Chen MagicPIG: LSH Sampling for Efficient LLM Generation
Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, Yang Zhou, Jianyu Zhang, Niklas Nolte, Yuandong Tian, Matthijs Douze, Leon Bottou, Zhihao Jia, Beidi Chen MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds
Leon Hetzel, Johanna Sommer, Bastian Rieck, Fabian J Theis, Stephan Günnemann Magnetic Preference Optimization: Achieving Last-Iterate Convergence for Language Model Alignment
Mingzhi Wang, Chengdong Ma, Qizhi Chen, Linjian Meng, Yang Han, Jiancong Xiao, Zhaowei Zhang, Jing Huo, Weijie J Su, Yaodong Yang Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing
Zhangchen Xu, Fengqing Jiang, Luyao Niu, Yuntian Deng, Radha Poovendran, Yejin Choi, Bill Yuchen Lin Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-Tuning
Chongjie Si, Xuehui Wang, Xue Yang, Zhengqin Xu, Qingyun Li, Jifeng Dai, Yu Qiao, Xiaokang Yang, Wei Shen Making Text Embedders Few-Shot Learners
Chaofan Li, Minghao Qin, Shitao Xiao, Jianlyu Chen, Kun Luo, Defu Lian, Yingxia Shao, Zheng Liu Making Transformer Decoders Better Differentiable Indexers
Wuchao Li, Kai Zheng, Defu Lian, Qi Liu, Wentian Bao, Enyun Yu, Yang Song, Han Li, Kun Gai MallowsPO: Fine-Tune Your LLM with Preference Dispersions
Haoxian Chen, Hanyang Zhao, Henry Lam, David Yao, Wenpin Tang MambaQuant: Quantizing the Mamba Family with Variance Aligned Rotation Methods
Zukang Xu, Yuxuan Yue, Xing Hu, Dawei Yang, Zhihang Yuan, Zixu Jiang, Zhixuan Chen, JiangyongYu, Xuchen, Sifan Zhou MamBEV: Enabling State Space Models to Learn Birds-Eye-View Representations
Hongyu Ke, Jack Morris, Kentaro Oguchi, Xiaofei Cao, Yongkang Liu, Haoxin Wang, Yi Ding Manifold Constraint Reduces Exposure Bias in Accelerated Diffusion Sampling
Yuzhe Yao, Jun Chen, Zeyi Huang, Haonan Lin, Mengmeng Wang, Guang Dai, Jingdong Wang Manifold Induced Biases for Zero-Shot and Few-Shot Detection of Generated Images
Jonathan Brokman, Amit Giloni, Omer Hofman, Roman Vainshtein, Hisashi Kojima, Guy Gilboa MANTRA: The Manifold Triangulations Assemblage
Rubén Ballester, Ernst Röell, Daniel Bin Schmid, Mathieu Alain, Sergio Escalera, Carles Casacuberta, Bastian Rieck Many-Objective Multi-Solution Transport
Ziyue Li, Tian Li, Virginia Smith, Jeff Bilmes, Tianyi Zhou MAP: Low-Compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation
Lu Li, Tianyu Zhang, Zhiqi Bu, Suyuchen Wang, Huan He, Jie Fu, Yonghui Wu, Jiang Bian, Yong Chen, Yoshua Bengio MAP: Multi-Human-Value Alignment Palette
Xinran Wang, Qi Le, Ammar Ahmed, Enmao Diao, Yi Zhou, Nathalie Baracaldo, Jie Ding, Ali Anwar MAPS: Advancing Multi-Modal Reasoning in Expert-Level Physical Science
Erle Zhu, Yadi Liu, Zhe Zhang, Xujun Li, JinZhou, Xinjie Yu, Minlie Huang, Hongning Wang Masked Temporal Interpolation Diffusion for Procedure Planning in Instructional Videos
Yufan Zhou, Zhaobo Qi, Lingshuai Lin, Junqi Jing, Tingting Chai, Beichen Zhang, Shuhui Wang, Weigang Zhang MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer
Yuancheng Wang, Haoyue Zhan, Liwei Liu, Ruihong Zeng, Haotian Guo, Jiachen Zheng, Qiang Zhang, Xueyao Zhang, Shunsi Zhang, Zhizheng Wu MAST: Model-Agnostic Sparsified Training
Yury Demidovich, Grigory Malinovsky, Egor Shulgin, Peter Richtárik Mastering Task Arithmetic: $\tau$Jp as a Key Indicator for Weight Disentanglement
Kotaro Yoshida, Yuji Naraki, Takafumi Horie, Ryosuke Yamaki, Ryotaro Shimizu, Yuki Saito, Julian McAuley, Hiroki Naganuma MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs
Andreas Opedal, Haruki Shirakami, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan Matrix Product Sketching via Coordinated Sampling
Majid Daliri, Juliana Freire, Danrong Li, Christopher Musco Matryoshka Multimodal Models
Mu Cai, Jianwei Yang, Jianfeng Gao, Yong Jae Lee MatryoshkaKV: Adaptive KV Compression via Trainable Orthogonal Projection
Bokai Lin, Zihao Zeng, Zipeng Xiao, Siqi Kou, TianQi Hou, Xiaofeng Gao, Hao Zhang, Zhijie Deng MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine
Renrui Zhang, Xinyu Wei, Dongzhi Jiang, Ziyu Guo, Yichi Zhang, Chengzhuo Tong, Jiaming Liu, Aojun Zhou, Shanghang Zhang, Peng Gao, Hongsheng Li Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory
Aymane El Firdoussi, Mohamed El Amine Seddik, Soufiane Hayou, Reda Alami, Ahmed Alzubaidi, Hakim Hacid McEval: Massively Multilingual Code Evaluation
Linzheng Chai, Shukai Liu, Jian Yang, Yuwei Yin, JinKe, Jiaheng Liu, Tao Sun, Ge Zhang, Changyu Ren, Hongcheng Guo, Noah Wang, Boyang Wang, Xianjie Wu, Bing Wang, Tongliang Li, Liqun Yang, Sufeng Duan, Zhaoxiang Zhang, Zhoujun Li MCNC: Manifold-Constrained Reparameterization for Neural Compression
Chayne Thrash, Reed Andreas, Ali Abbasi, Parsa Nooralinejad, Soroush Abbasi Koohpayegani, Hamed Pirsiavash, Soheil Kolouri Measuring and Improving Engagement of Text-to-Image Generation Models
Varun Khurana, Yaman Kumar Singla, Jayakumar Subramanian, Changyou Chen, Rajiv Ratn Shah, Zhiqiang Xu, Balaji Krishnamurthy Measuring and Improving Persuasiveness of Large Language Models
Somesh Kumar Singh, Yaman Kumar Singla, S I Harini, Balaji Krishnamurthy Measuring Memorization in RLHF for Code Completion
Jamie Hayes, Ilia Shumailov, William P. Porter, Aneesh Pappu Measuring Non-Adversarial Reproduction of Training Data in Large Language Models
Michael Aerni, Javier Rando, Edoardo Debenedetti, Nicholas Carlini, Daphne Ippolito, Florian Tramèr MedTrinity-25m: A Large-Scale Multimodal Dataset with Multigranular Annotations for Medicine
Yunfei Xie, Ce Zhou, Lang Gao, Juncheng Wu, Xianhang Li, Hong-Yu Zhou, Sheng Liu, Lei Xing, James Zou, Cihang Xie, Yuyin Zhou MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks
Jiacheng Chen, Tianhao Liang, Sherman Siu, Zhengqing Wang, Kai Wang, Yubo Wang, Yuansheng Ni, Ziyan Jiang, Wang Zhu, Bohan Lyu, Dongfu Jiang, Xuan He, Yuan Liu, Hexiang Hu, Xiang Yue, Wenhu Chen MELODI: Exploring Memory Compression for Long Contexts
Yinpeng Chen, DeLesley Hutchins, Aren Jansen, Andrey Zhmoginov, David Racz, Jesper Sparre Andersen Memory Mosaics
Jianyu Zhang, Niklas Nolte, Ranajoy Sadhukhan, Beidi Chen, Leon Bottou MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers
Yiwen Chen, Tong He, Di Huang, Weicai Ye, Sijin Chen, Jiaxiang Tang, Zhongang Cai, Lei Yang, Gang Yu, Guosheng Lin, Chi Zhang Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold
Lazar Atanackovic, Xi Zhang, Brandon Amos, Mathieu Blanchette, Leo J Lee, Yoshua Bengio, Alexander Tong, Kirill Neklyudov Meta-Continual Learning of Neural Fields
Seungyoon Woo, Junhyeog Yun, Gunhee Kim Meta-Dynamical State Space Models for Integrative Neural Data Analysis
Ayesha Vermani, Josue Nassar, Hyungju Jeon, Matthew Dowling, Il Memming Park MetaDesigner: Advancing Artistic Typography Through AI-Driven, User-Centric, and Multilingual WordArt Synthesis
Jun-Yan He, Zhi-Qi Cheng, Chenyang Li, Jingdong Sun, Qi He, Wangmeng Xiang, Hanyuan Chen, Jin-Peng Lan, Xianhui Lin, Kang Zhu, Bin Luo, Yifeng Geng, Xuansong Xie, Alexander G Hauptmann Metalic: Meta-Learning In-Context with Protein Language Models
Jacob Beck, Shikha Surana, Manus McAuliffe, Oliver Bent, Thomas D Barrett, Juan Jose Garau-Luis, Paul Duckworth MetaMetrics: Calibrating Metrics for Generation Tasks Using Human Preferences
Genta Indra Winata, David Anugraha, Lucky Susanto, Garry Kuwanto, Derry Tanti Wijaya MetaOOD: Automatic Selection of OOD Detection Models
Yuehan Qin, Yichi Zhang, Yi Nian, Xueying Ding, Yue Zhao MetaUrban: An Embodied AI Simulation Platform for Urban Micromobility
Wayne Wu, Honglin He, Jack He, Yiran Wang, Chenda Duan, Zhizheng Liu, Quanyi Li, Bolei Zhou Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity
Eduard Gorbunov, Nazarii Tupitsa, Sayantan Choudhury, Alen Aliev, Peter Richtárik, Samuel Horváth, Martin Takáč Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization
Yury Demidovich, Petr Ostroukhov, Grigory Malinovsky, Samuel Horváth, Martin Takáč, Peter Richtárik, Eduard Gorbunov MeToken: Uniform Micro-Environment Token Boosts Post-Translational Modification Prediction
Cheng Tan, Zhenxiao Cao, Zhangyang Gao, Lirong Wu, Siyuan Li, Yufei Huang, Jun Xia, Bozhen Hu, Stan Z. Li MIA-Bench: Towards Better Instruction Following Evaluation of Multimodal LLMs
Yusu Qian, Hanrong Ye, Jean-Philippe Fauconnier, Peter Grasch, Yinfei Yang, Zhe Gan MIA-DPO: Multi-Image Augmented Direct Preference Optimization for Large Vision-Language Models
Ziyu Liu, Yuhang Zang, Xiaoyi Dong, Pan Zhang, Yuhang Cao, Haodong Duan, Conghui He, Yuanjun Xiong, Dahua Lin, Jiaqi Wang Min-K%++: Improved Baseline for Pre-Training Data Detection from Large Language Models
Jingyang Zhang, Jingwei Sun, Eric Yeats, Yang Ouyang, Martin Kuo, Jianyi Zhang, Hao Frank Yang, Hai Li Mind Control Through Causal Inference: Predicting Clean Images from Poisoned Data
Mengxuan Hu, Zihan Guan, Yi Zeng, Junfeng Guo, Zhongliang Zhou, Jielu Zhang, Ruoxi Jia, Anil Kumar Vullikanti, Sheng Li Mind the Gap: Examining the Self-Improvement Capabilities of Large Language Models
Yuda Song, Hanlin Zhang, Carson Eisenach, Sham M. Kakade, Dean Foster, Udaya Ghai MIND: Math Informed syNthetic Dialogues for Pretraining LLMs
Syeda Nahida Akter, Shrimai Prabhumoye, John Kamalu, Sanjeev Satheesh, Eric Nyberg, Mostofa Patwary, Mohammad Shoeybi, Bryan Catanzaro MindSearch: Mimicking Human Minds Elicits Deep AI Searcher
Zehui Chen, Kuikun Liu, Qiuchen Wang, Jiangning Liu, Wenwei Zhang, Kai Chen, Feng Zhao Minimal Impact ControlNet: Advancing Multi-ControlNet Integration
Shikun Sun, Min Zhou, Zixuan Wang, Xubin Li, Tiezheng Ge, Zijie Ye, Xiaoyu Qin, Junliang Xing, Bo Zheng, Jia Jia Mining Your Own Secrets: Diffusion Classifier Scores for Continual Personalization of Text-to-Image Diffusion Models
Saurav Jha, Shiqi Yang, Masato Ishii, Mengjie Zhao, Christian Simon, Muhammad Jehanzeb Mirza, Dong Gong, Lina Yao, Shusuke Takahashi, Yuki Mitsufuji Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization
Sascha Marton, Tim Grams, Florian Vogt, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt Mitigating Memorization in Language Models
Mansi Sakarvadia, Aswathy Ajith, Arham Mushtaq Khan, Nathaniel C Hudson, Caleb Geniesse, Kyle Chard, Yaoqing Yang, Ian Foster, Michael W. Mahoney Mitigating Object Hallucination in MLLMs via Data-Augmented Phrase-Level Alignment
Pritam Sarkar, Sayna Ebrahimi, Ali Etemad, Ahmad Beirami, Sercan O Arik, Tomas Pfister MixEval-X: Any-to-Any Evaluations from Real-World Data Mixture
Jinjie Ni, Yifan Song, Deepanway Ghosal, Bo Li, David Junhao Zhang, Xiang Yue, Fuzhao Xue, Yuntian Deng, Zian Zheng, Kaichen Zhang, Mahir Shah, Kabir Jain, Yang You, Michael Shieh Mixture Compressor for Mixture-of-Experts LLMs Gains More
Wei Huang, Yue Liao, Jianhui Liu, Ruifei He, Haoru Tan, Shiming Zhang, Hongsheng Li, Si Liu, Xiaojuan Qi Mixture of Attentions for Speculative Decoding
Matthieu Zimmer, Milan Gritta, Gerasimos Lampouras, Haitham Bou Ammar, Jun Wang Mixture of In-Context Prompters for Tabular PFNs
Derek Qiang Xu, F Olcay Cirit, Reza Asadi, Yizhou Sun, Wei Wang Mixture of Parrots: Experts Improve Memorization More than Reasoning
Samy Jelassi, Clara Mohri, David Brandfonbrener, Alex Gu, Nikhil Vyas, Nikhil Anand, David Alvarez-Melis, Yuanzhi Li, Sham M. Kakade, Eran Malach Mixture-of-Agents Enhances Large Language Model Capabilities
Junlin Wang, Jue Wang, Ben Athiwaratkun, Ce Zhang, James Zou MLE-Bench: Evaluating Machine Learning Agents on Machine Learning Engineering
Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, James Aung, Dane Sherburn, Evan Mays, Giulio Starace, Kevin Liu, Leon Maksin, Tejal Patwardhan, Aleksander Madry, Lilian Weng MLLM Can See? Dynamic Correction Decoding for Hallucination Mitigation
Chenxi Wang, Xiang Chen, Ningyu Zhang, Bozhong Tian, Haoming Xu, Shumin Deng, Huajun Chen Mm-Embed: Universal Multimodal Retrieval with Multimodal LLMs
Sheng-Chieh Lin, Chankyu Lee, Mohammad Shoeybi, Jimmy Lin, Bryan Catanzaro, Wei Ping MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-Tuning
Haotian Zhang, Mingfei Gao, Zhe Gan, Philipp Dufter, Nina Wenzel, Forrest Huang, Dhruti Shah, Xianzhi Du, Bowen Zhang, Yanghao Li, Sam Dodge, Keen You, Zhen Yang, Aleksei Timofeev, Mingze Xu, Hong-You Chen, Jean-Philippe Fauconnier, Zhengfeng Lai, Haoxuan You, Zirui Wang, Afshin Dehghan, Peter Grasch, Yinfei Yang MMAD: A Comprehensive Benchmark for Multimodal Large Language Models in Industrial Anomaly Detection
Xi Jiang, Jian Li, Hanqiu Deng, Yong Liu, Bin-Bin Gao, Yifeng Zhou, Jialin Li, Chengjie Wang, Feng Zheng MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark
S Sakshi, Utkarsh Tyagi, Sonal Kumar, Ashish Seth, Ramaneswaran Selvakumar, Oriol Nieto, Ramani Duraiswami, Sreyan Ghosh, Dinesh Manocha MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
Chejian Xu, Jiawei Zhang, Zhaorun Chen, Chulin Xie, Mintong Kang, Yujin Potter, Zhun Wang, Zhuowen Yuan, Alexander Xiong, Zidi Xiong, Chenhui Zhang, Lingzhi Yuan, Yi Zeng, Peiyang Xu, Chengquan Guo, Andy Zhou, Jeffrey Ziwei Tan, Xuandong Zhao, Francesco Pinto, Zhen Xiang, Yu Gai, Zinan Lin, Dan Hendrycks, Bo Li, Dawn Song MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios That Are Difficult for Humans?
YiFan Zhang, Huanyu Zhang, Haochen Tian, Chaoyou Fu, Shuangqing Zhang, Junfei Wu, Feng Li, Kun Wang, Qingsong Wen, Zhang Zhang, Liang Wang, Rong Jin MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
Peng Xia, Kangyu Zhu, Haoran Li, Tianze Wang, Weijia Shi, Sheng Wang, Linjun Zhang, James Zou, Huaxiu Yao MMEgo: Towards Building Egocentric Multimodal LLMs for Video QA
Hanrong Ye, Haotian Zhang, Erik Daxberger, Lin Chen, Zongyu Lin, Yanghao Li, Bowen Zhang, Haoxuan You, Dan Xu, Zhe Gan, Jiasen Lu, Yinfei Yang MMFakeBench: A Mixed-Source Multimodal Misinformation Detection Benchmark for LVLMs
Xuannan Liu, Zekun Li, Pei Pei Li, Huaibo Huang, Shuhan Xia, Xing Cui, Linzhi Huang, Weihong Deng, Zhaofeng He MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Models
Peng Xia, Siwei Han, Shi Qiu, Yiyang Zhou, Zhaoyang Wang, Wenhao Zheng, Zhaorun Chen, Chenhang Cui, Mingyu Ding, Linjie Li, Lijuan Wang, Huaxiu Yao MMIU: Multimodal Multi-Image Understanding for Evaluating Large Vision-Language Models
Fanqing Meng, Jin Wang, Chuanhao Li, Quanfeng Lu, Hao Tian, Tianshuo Yang, Jiaqi Liao, Xizhou Zhu, Jifeng Dai, Yu Qiao, Ping Luo, Kaipeng Zhang, Wenqi Shao MMKE-Bench: A Multimodal Editing Benchmark for Diverse Visual Knowledge
Yuntao Du., Kailin Jiang, Zhi Gao, Chenrui Shi, Zilong Zheng, Siyuan Qi, Qing Li MMQA: Evaluating LLMs with Multi-Table Multi-Hop Complex Questions
Jian Wu, Linyi Yang, Dongyuan Li, Yuliang Ji, Manabu Okumura, Yue Zhang MMSearch: Unveiling the Potential of Large Models as Multi-Modal Search Engines
Dongzhi Jiang, Renrui Zhang, Ziyu Guo, Yanmin Wu, Jiayi Lei, Pengshuo Qiu, Pan Lu, Zehui Chen, Guanglu Song, Peng Gao, Yu Liu, Chunyuan Li, Hongsheng Li MMTEB: Massive Multilingual Text Embedding Benchmark
Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, Márton Kardos, Ashwin Mathur, David Stap, Jay Gala, Wissam Siblini, Dominik Krzemiński, Genta Indra Winata, Saba Sturua, Saiteja Utpala, Mathieu Ciancone, Marion Schaeffer, Diganta Misra, Shreeya Dhakal, Jonathan Rystrøm, Roman Solomatin, Ömer Veysel Çağatan, Akash Kundu, Martin Bernstorff, Shitao Xiao, Akshita Sukhlecha, Bhavish Pahwa, Rafał Poświata, Kranthi Kiran Gv, Shawon Ashraf, Daniel Auras, Björn Plüster, Jan Philipp Harries, Loïc Magne, Isabelle Mohr, Dawei Zhu, Hippolyte Gisserot-Boukhlef, Tom Aarsen, Jan Kostkan, Konrad Wojtasik, Taemin Lee, Marek Suppa, Crystina Zhang, Roberta Rocca, Mohammed Hamdy, Andrianos Michail, John Yang, Manuel Faysse, Aleksei Vatolin, Nandan Thakur, Manan Dey, Dipam Vasani, Pranjal A Chitale, Simone Tedeschi, Nguyen Tai, Artem Snegirev, Mariya Hendriksen, Michael Günther, Mengzhou Xia, Weijia Shi, Xing Han Lù, Jordan Clive, Gayatri K, Maksimova Anna, Silvan Wehrli, Maria Tikhonova, Henil Shalin Panchal, Aleksandr Abramov, Malte Ostendorff, Zheng Liu, Simon Clematide, Lester James Validad Miranda, Alena Fenogenova, Guangyu Song, Ruqiya Bin Safi, Wen-Ding Li, Alessia Borghini, Federico Cassano, Lasse Hansen, Sara Hooker, Chenghao Xiao, Vaibhav Adlakha, Orion Weller, Siva Reddy, Niklas Muennighoff MMWorld: Towards Multi-Discipline Multi-Faceted World Model Evaluation in Videos
Xuehai He, Weixi Feng, Kaizhi Zheng, Yujie Lu, Wanrong Zhu, Jiachen Li, Yue Fan, Jianfeng Wang, Linjie Li, Zhengyuan Yang, Kevin Lin, William Yang Wang, Lijuan Wang, Xin Eric Wang Modality-Specialized Synergizers for Interleaved Vision-Language Generalists
Zhiyang Xu, Minqian Liu, Ying Shen, Joy Rimchala, Jiaxin Zhang, Qifan Wang, Yu Cheng, Lifu Huang MoDeGPT: Modular Decomposition for Large Language Model Compression
Chi-Heng Lin, Shangqian Gao, James Seale Smith, Abhishek Patel, Shikhar Tuli, Yilin Shen, Hongxia Jin, Yen-Chang Hsu Model Merging with SVD to Tie the Knots
George Stoica, Pratik Ramesh, Boglarka Ecsedi, Leshem Choshen, Judy Hoffman Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout
Bharat Srikishan, Daniel O'Malley, Mohamed Mehana, Nicholas Lubbers, Nikhil Muralidhar Modeling Complex System Dynamics with Flow Matching Across Time and Conditions
Martin Rohbeck, Edward De Brouwer, Charlotte Bunne, Jan-Christian Huetter, Anne Biton, Kelvin Y. Chen, Aviv Regev, Romain Lopez Modeling Fine-Grained Hand-Object Dynamics for Egocentric Video Representation Learning
Baoqi Pei, Yifei Huang, Jilan Xu, Guo Chen, Yuping He, Lijin Yang, Yali Wang, Weidi Xie, Yu Qiao, Fei Wu, Limin Wang Monet: Mixture of Monosemantic Experts for Transformers
Jungwoo Park, Ahn Young Jin, Kee-Eung Kim, Jaewoo Kang MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion
Junyi Zhang, Charles Herrmann, Junhwa Hur, Varun Jampani, Trevor Darrell, Forrester Cole, Deqing Sun, Ming-Hsuan Yang MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses
Zonglin Yang, Wanhao Liu, Ben Gao, Tong Xie, Yuqiang Li, Wanli Ouyang, Soujanya Poria, Erik Cambria, Dongzhan Zhou Moral Alignment for LLM Agents
Elizaveta Tennant, Stephen Hailes, Mirco Musolesi MorphoDiff: Cellular Morphology Painting with Diffusion Models
Zeinab Navidi, Jun Ma, Esteban Miglietta, Le Liu, Anne E Carpenter, Beth A Cimini, Benjamin Haibe-Kains, Bo Wang MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection
Zhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh, Yonggang Zhang, Zi Huang, Yadan Luo MoS: Unleashing Parameter Efficiency of Low-Rank Adaptation with Mixture of Shards
Sheng Wang, Liheng Chen, Pengan Chen, Jingwei Dong, Boyang Xue, Jiyue Jiang, Lingpeng Kong, Chuan Wu MotionClone: Training-Free Motion Cloning for Controllable Video Generation
Pengyang Ling, Jiazi Bu, Pan Zhang, Xiaoyi Dong, Yuhang Zang, Tong Wu, Huaian Chen, Jiaqi Wang, Yi Jin MotionDreamer: One-to-Many Motion Synthesis with Localized Generative Masked Transformer
Yilin Wang, Chuan Guo, Yuxuan Mu, Muhammad Gohar Javed, Xinxin Zuo, Juwei Lu, Hai Jiang, Li Cheng MovieDreamer: Hierarchical Generation for Coherent Long Visual Sequences
Canyu Zhao, Mingyu Liu, Wen Wang, Weihua Chen, Fan Wang, Hao Chen, Bo Zhang, Chunhua Shen mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models
Jiabo Ye, Haiyang Xu, Haowei Liu, Anwen Hu, Ming Yan, Qi Qian, Ji Zhang, Fei Huang, Jingren Zhou MQuAKE-Remastered: Multi-Hop Knowledge Editing Can Only Be Advanced with Reliable Evaluations
Shaochen Zhong, Yifan Lu, Lize Shao, Bhargav Bhushanam, Xiaocong Du, Yixin Wan, Yucheng Shi, Daochen Zha, Yiwei Wang, Ninghao Liu, Kaixiong Zhou, Shuai Xu, Kai-Wei Chang, Louis Feng, Vipin Chaudhary, Xia Hu MRAG-Bench: Vision-Centric Evaluation for Retrieval-Augmented Multimodal Models
Wenbo Hu, Jia-Chen Gu, Zi-Yi Dou, Mohsen Fayyaz, Pan Lu, Kai-Wei Chang, Nanyun Peng MrT5: Dynamic Token Merging for Efficient Byte-Level Language Models
Julie Kallini, Shikhar Murty, Christopher D Manning, Christopher Potts, Róbert Csordás MTU-Bench: A Multi-Granularity Tool-Use Benchmark for Large Language Models
Pei Wang, Yanan Wu, Noah Wang, Jiaheng Liu, Xiaoshuai Song, Z.Y. Peng, Ken Deng, Chenchen Zhang, JiakaiWang, Junran Peng, Ge Zhang, Hangyu Guo, Zhaoxiang Zhang, Wenbo Su, Bo Zheng MuHBoost: Multi-Label Boosting for Practical Longitudinal Human Behavior Modeling
Nguyen T Thach, Patrick Habecker, Anika R. Eisenbraun, W. Alex Mason, Kimberly A. Tyler, Bilal Khan, Hau Chan MuirBench: A Comprehensive Benchmark for Robust Multi-Image Understanding
Fei Wang, Xingyu Fu, James Y. Huang, Zekun Li, Qin Liu, Xiaogeng Liu, Mingyu Derek Ma, Nan Xu, Wenxuan Zhou, Kai Zhang, Tianyi Lorena Yan, Wenjie Jacky Mo, Hsiang-Hui Liu, Pan Lu, Chunyuan Li, Chaowei Xiao, Kai-Wei Chang, Dan Roth, Sheng Zhang, Hoifung Poon, Muhao Chen Multi-Agent Cooperation Through Learning-Aware Policy Gradients
Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer, Eric Elmoznino, Blake Aaron Richards, Guillaume Lajoie, Blaise Aguera y Arcas, Joao Sacramento Multi-Dimensional Conformal Prediction
Yam Tawachi, Bracha Laufer-Goldshtein Multi-Domain Distribution Learning for De Novo Drug Design
Arne Schneuing, Ilia Igashov, Adrian W. Dobbelstein, Thomas Castiglione, Michael M. Bronstein, Bruno Correia Multi-Draft Speculative Sampling: Canonical Decomposition and Theoretical Limits
Ashish J Khisti, MohammadReza Ebrahimi, Hassan Dbouk, Arash Behboodi, Roland Memisevic, Christos Louizos Multi-Field Adaptive Retrieval
Millicent Li, Tongfei Chen, Benjamin Van Durme, Patrick Xia Multi-Label Node Classification with Label Influence Propagation
Yifei Sun, Zemin Liu, Bryan Hooi, Yang Yang, Rizal Fathony, Jia Chen, Bingsheng He Multi-Level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning
Shijie Liu, Andrew Craig Cullen, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein Multi-Modal Agent Tuning: Building a VLM-Driven Agent for Efficient Tool Usage
Zhi Gao, Bofei Zhang, Pengxiang Li, Xiaojian Ma, Tao Yuan, Yue Fan, Yuwei Wu, Yunde Jia, Song-Chun Zhu, Qing Li Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen
Alessandro Palma, Till Richter, Hanyi Zhang, Manuel Lubetzki, Alexander Tong, Andrea Dittadi, Fabian J Theis Multi-Modal Brain Encoding Models for Multi-Modal Stimuli
Subba Reddy Oota, Khushbu Pahwa, Mounika Marreddy, Maneesh Kumar Singh, Manish Gupta, Bapi Raju Surampudi Multi-Objective Differentiable Neural Architecture Search
Rhea Sanjay Sukthanker, Arber Zela, Benedikt Staffler, Samuel Dooley, Josif Grabocka, Frank Hutter Multi-Perspective Data Augmentation for Few-Shot Object Detection
Anh Khoa Nguyen Vu, Truong Quoc Truong, Vinh-Tiep Nguyen, Thanh Duc Ngo, Thanh-Toan Do, Tam V. Nguyen Multi-Reward as Condition for Instruction-Based Image Editing
Xin Gu, Ming Li, Libo Zhang, Fan Chen, Longyin Wen, Tiejian Luo, Sijie Zhu Multi-Robot Motion Planning with Diffusion Models
Yorai Shaoul, Itamar Mishani, Shivam Vats, Jiaoyang Li, Maxim Likhachev Multi-Scale Fusion for Object Representation
Rongzhen Zhao, Vivienne Huiling Wang, Juho Kannala, Joni Pajarinen Multi-Session, Multi-Task Neural Decoding from Distinct Cell-Types and Brain Regions
Mehdi Azabou, Krystal Xuejing Pan, Vinam Arora, Ian Jarratt Knight, Eva L Dyer, Blake Aaron Richards Multi-Task Dense Predictions via Unleashing the Power of Diffusion
Yuqi Yang, Peng-Tao Jiang, Qibin Hou, Hao Zhang, Jinwei Chen, Bo Li Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains
Vighnesh Subramaniam, Yilun Du, Joshua B. Tenenbaum, Antonio Torralba, Shuang Li, Igor Mordatch Multilevel Generative Samplers for Investigating Critical Phenomena
Ankur Singha, Elia Cellini, Kim Andrea Nicoli, Karl Jansen, Stefan Kühn, Shinichi Nakajima Multimodal Quantitative Language for Generative Recommendation
Jianyang Zhai, Zi-Feng Mai, Chang-Dong Wang, Feidiao Yang, Xiawu Zheng, Hui Li, Yonghong Tian Multimodal Situational Safety
Kaiwen Zhou, Chengzhi Liu, Xuandong Zhao, Anderson Compalas, Dawn Song, Xin Eric Wang Multimodality Helps Few-Shot 3D Point Cloud Semantic Segmentation
Zhaochong An, Guolei Sun, Yun Liu, Runjia Li, Min Wu, Ming-Ming Cheng, Ender Konukoglu, Serge Belongie MuPT: A Generative Symbolic Music Pretrained Transformer
Xingwei Qu, Yuelin Bai, Yinghao Ma, Ziya Zhou, Ka Man Lo, Jiaheng Liu, Ruibin Yuan, Lejun Min, Xueling Liu, Tianyu Zhang, Xeron Du, Shuyue Guo, Yiming Liang, Yizhi Li, Shangda Wu, Junting Zhou, Tianyu Zheng, Ziyang Ma, Fengze Han, Wei Xue, Gus Xia, Emmanouil Benetos, Xiang Yue, Chenghua Lin, Xu Tan, Wenhao Huang, Jie Fu, Ge Zhang MUSE: Machine Unlearning Six-Way Evaluation for Language Models
Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman, Daogao Liu, Luke Zettlemoyer, Noah A. Smith, Chiyuan Zhang MuseGNN: Forming Scalable, Convergent GNN Layers That Minimize a Sampling-Based Energy
Haitian Jiang, Renjie Liu, Zengfeng Huang, Yichuan Wang, Xiao Yan, Zhenkun Cai, Minjie Wang, David Wipf Mutual Effort for Efficiency: A Similarity-Based Token Pruning for Vision Transformers in Self-Supervised Learning
Sheng Li, Qitao Tan, Yue Dai, Zhenglun Kong, Tianyu Wang, Jun Liu, Ao Li, Ninghao Liu, Yufei Ding, Xulong Tang, Geng Yuan Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solver
Zhenting Qi, Mingyuan Ma, Jiahang Xu, Li Lyna Zhang, Fan Yang, Mao Yang NarrativeBridge: Enhancing Video Captioning with Causal-Temporal Narrative
Asmar Nadeem, Faegheh Sardari, Robert Dawes, Syed Sameed Husain, Adrian Hilton, Armin Mustafa Natural Language Inference Improves Compositionality in Vision-Language Models
Paola Cascante-Bonilla, Yu Hou, Yang Trista Cao, Hal Daumé Iii, Rachel Rudinger Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence
Frederik Pahde, Maximilian Dreyer, Moritz Weckbecker, Leander Weber, Christopher J. Anders, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents
Boyu Gou, Ruohan Wang, Boyuan Zheng, Yanan Xie, Cheng Chang, Yiheng Shu, Huan Sun, Yu Su Near-Exact Privacy Amplification for Matrix Mechanisms
Christopher A. Choquette-Choo, Arun Ganesh, Saminul Haque, Thomas Steinke, Abhradeep Guha Thakurta Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form
Toshinori Kitamura, Tadashi Kozuno, Wataru Kumagai, Kenta Hoshino, Yohei Hosoe, Kazumi Kasaura, Masashi Hamaya, Paavo Parmas, Yutaka Matsuo Near, Far: Patch-Ordering Enhances Vision Foundation Models' Scene Understanding
Valentinos Pariza, Mohammadreza Salehi, Gertjan J. Burghouts, Francesco Locatello, Yuki M Asano Needle in a Video Haystack: A Scalable Synthetic Evaluator for Video MLLMs
Zijia Zhao, Haoyu Lu, Yuqi Huo, Yifan Du, Tongtian Yue, Longteng Guo, Bingning Wang, Weipeng Chen, Jing Liu NetMoE: Accelerating MoE Training Through Dynamic Sample Placement
Xinyi Liu, Yujie Wang, Fangcheng Fu, Xupeng Miao, Shenhan Zhu, Xiaonan Nie, Bin Cui Neural Causal Graph for Interpretable and Intervenable Classification
Jiawei Wang, Shaofei Lu, Da Cao, Dongyu Wang, Yuquan Le, Zhe Quan, Tat-Seng Chua Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low Neural Eulerian Scene Flow Fields
Kyle Vedder, Neehar Peri, Ishan Khatri, Siyi Li, Eric Eaton, Mehmet Kemal Kocamaz, Yue Wang, Zhiding Yu, Deva Ramanan, Joachim Pehserl Neural Fluid Simulation on Geometric Surfaces
Haoxiang Wang, Tao Yu, Hui Qiao, Qionghai Dai Neural Functions for Learning Periodic Signal
Woojin Cho, Minju Jo, Kookjin Lee, Noseong Park Neural Interactive Proofs
Lewis Hammond, Sam Adam-Day Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-Tuning
Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Duc Nguyen, Toan Tran, David Leo Wright Hall, Cheongwoong Kang, Jaesik Choi Neural Spacetimes for DAG Representation Learning
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein Neuron Based Personality Trait Induction in Large Language Models
Jia Deng, Tianyi Tang, Yanbin Yin, Wenhao Yang, Xin Zhao, Ji-Rong Wen Neuron-Based Multifractal Analysis of Neuron Interaction Dynamics in Large Models
Xiongye Xiao, Heng Ping, Chenyu Zhou, Defu Cao, Yaxing Li, Yi-Zhuo Zhou, Shixuan Li, Nikos Kanakaris, Paul Bogdan Neuroplastic Expansion in Deep Reinforcement Learning
Jiashun Liu, Johan Samir Obando Ceron, Aaron Courville, Ling Pan New Algorithms for the Learning-Augmented K-Means Problem
Junyu Huang, Qilong Feng, Ziyun Huang, Zhen Zhang, Jinhui Xu, Jianxin Wang NExT-Mol: 3D Diffusion Meets 1d Language Modeling for 3D Molecule Generation
Zhiyuan Liu, Yanchen Luo, Han Huang, Enzhi Zhang, Sihang Li, Junfeng Fang, Yaorui Shi, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua NextBestPath: Efficient 3D Mapping of Unseen Environments
Shiyao Li, Antoine Guedon, Clémentin Boittiaux, Shizhe Chen, Vincent Lepetit NL-Eye: Abductive NLI for Images
Mor Ventura, Michael Toker, Nitay Calderon, Zorik Gekhman, Yonatan Bitton, Roi Reichart NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals
Jaden Fried Fiotto-Kaufman, Alexander Russell Loftus, Eric Todd, Jannik Brinkmann, Koyena Pal, Dmitrii Troitskii, Michael Ripa, Adam Belfki, Can Rager, Caden Juang, Aaron Mueller, Samuel Marks, Arnab Sen Sharma, Francesca Lucchetti, Nikhil Prakash, Carla E. Brodley, Arjun Guha, Jonathan Bell, Byron C Wallace, David Bau No Need to Talk: Asynchronous Mixture of Language Models
Anastasiia Filippova, Angelos Katharopoulos, David Grangier, Ronan Collobert No Pose, No Problem: Surprisingly Simple 3D Gaussian Splats from Sparse Unposed Images
Botao Ye, Sifei Liu, Haofei Xu, Xueting Li, Marc Pollefeys, Ming-Hsuan Yang, Songyou Peng No Preference Left Behind: Group Distributional Preference Optimization
Binwei Yao, Zefan Cai, Yun-Shiuan Chuang, Shanglin Yang, Ming Jiang, Diyi Yang, Junjie Hu Noisy Test-Time Adaptation in Vision-Language Models
Chentao Cao, Zhun Zhong, Zhanke Zhou, Tongliang Liu, Yang Liu, Kun Zhang, Bo Han Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother, Irina Rish, Glen Berseth, Sanjiban Choudhury Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson–Romberg Extrapolation
Marina Sheshukova, Denis Belomestny, Alain Oliviero Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov Not All Language Model Features Are One-Dimensionally Linear
Joshua Engels, Eric J Michaud, Isaac Liao, Wes Gurnee, Max Tegmark Not-so-Optimal Transport Flows for 3D Point Cloud Generation
Ka-Hei Hui, Chao Liu, Xiaohui Zeng, Chi-Wing Fu, Arash Vahdat NovelQA: Benchmarking Question Answering on Documents Exceeding 200k Tokens
Cunxiang Wang, Ruoxi Ning, Boqi Pan, Tonghui Wu, Qipeng Guo, Cheng Deng, Guangsheng Bao, Xiangkun Hu, Zheng Zhang, Qian Wang, Yue Zhang Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning
Caleb Chuck, Fan Feng, Carl Qi, Chang Shi, Siddhant Agarwal, Amy Zhang, Scott Niekum NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models
Chankyu Lee, Rajarshi Roy, Mengyao Xu, Jonathan Raiman, Mohammad Shoeybi, Bryan Catanzaro, Wei Ping OCEAN: Offline Chain-of-Thought Evaluation and Alignment in Large Language Models
Junda Wu, Xintong Li, Ruoyu Wang, Yu Xia, Yuxin Xiong, Jianing Wang, Tong Yu, Xiang Chen, Branislav Kveton, Lina Yao, Jingbo Shang, Julian McAuley ODE-Based Smoothing Neural Network for Reinforcement Learning Tasks
Yinuo Wang, Wenxuan Wang, Xujie Song, Tong Liu, Yuming Yin, Liangfa Chen, Likun Wang, Jingliang Duan, Shengbo Eben Li Offline Hierarchical Reinforcement Learning via Inverse Optimization
Carolin Schmidt, Daniele Gammelli, James Harrison, Marco Pavone, Filipe Rodrigues Offline Model-Based Optimization by Learning to Rank
Rong-Xi Tan, Ke Xue, Shen-Huan Lyu, Haopu Shang, Yaowang, Yaoyuan Wang, Fu Sheng, Chao Qian Offline RL in Regular Decision Processes: Sample Efficiency via Language Metrics
Ahana Deb, Roberto Cipollone, Anders Jonsson, Alessandro Ronca, Mohammad Sadegh Talebi Offline RL with Smooth OOD Generalization in Convex Hull and Its Neighborhood
Qingmao Yao, Zhichao Lei, Tianyuan Chen, Ziyue Yuan, Xuefan Chen, Jianxiang Liu, Faguo Wu, Xiao Zhang OGBench: Benchmarking Offline Goal-Conditioned RL
Seohong Park, Kevin Frans, Benjamin Eysenbach, Sergey Levine OLMoE: Open Mixture-of-Experts Language Models
Niklas Muennighoff, Luca Soldaini, Dirk Groeneveld, Kyle Lo, Jacob Morrison, Sewon Min, Weijia Shi, Evan Pete Walsh, Oyvind Tafjord, Nathan Lambert, Yuling Gu, Shane Arora, Akshita Bhagia, Dustin Schwenk, David Wadden, Alexander Wettig, Binyuan Hui, Tim Dettmers, Douwe Kiela, Ali Farhadi, Noah A. Smith, Pang Wei Koh, Amanpreet Singh, Hannaneh Hajishirzi OMG: Opacity Matters in Material Modeling with Gaussian Splatting
Silong Yong, Venkata Nagarjun Pudureddiyur Manivannan, Bernhard Kerbl, Zifu Wan, Simon Stepputtis, Katia P. Sycara, Yaqi Xie Omni-MATH: A Universal Olympiad Level Mathematic Benchmark for Large Language Models
Bofei Gao, Feifan Song, Zhe Yang, Zefan Cai, Yibo Miao, Qingxiu Dong, Lei Li, Chenghao Ma, Liang Chen, Runxin Xu, Zhengyang Tang, Benyou Wang, Daoguang Zan, Shanghaoran Quan, Ge Zhang, Lei Sha, Yichang Zhang, Xuancheng Ren, Tianyu Liu, Baobao Chang OmniBind: Large-Scale Omni Multimodal Representation via Binding Spaces
Zehan Wang, Ziang Zhang, Minjie Hong, Hang Zhang, Luping Liu, Rongjie Huang, Xize Cheng, Shengpeng Ji, Tao Jin, Hengshuang Zhao, Zhou Zhao OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text
Qingyun Li, Zhe Chen, Weiyun Wang, Wenhai Wang, Shenglong Ye, Zhenjiang Jin, Guanzhou Chen, Yinan He, Zhangwei Gao, Erfei Cui, Jiashuo Yu, Hao Tian, Jiasheng Zhou, Chao Xu, Bin Wang, Xingjian Wei, Wei Li, Wenjian Zhang, Bo Zhang, Pinlong Cai, Licheng Wen, Xiangchao Yan, Pei Chu, Yi Wang, Min Dou, Changyao Tian, Xizhou Zhu, Lewei Lu, Yushi Chen, Junjun He, Tong Lu, Yali Wang, Limin Wang, Dahua Lin, Yu Qiao, Botian Shi, Conghui He, Jifeng Dai OmniKV: Dynamic Context Selection for Efficient Long-Context LLMs
Jitai Hao, Yuke Zhu, Tian Wang, Jun Yu, Xin Xin, Bo Zheng, Zhaochun Ren, Sheng Guo OmniRe: Omni Urban Scene Reconstruction
Ziyu Chen, Jiawei Yang, Jiahui Huang, Riccardo de Lutio, Janick Martinez Esturo, Boris Ivanovic, Or Litany, Zan Gojcic, Sanja Fidler, Marco Pavone, Li Song, Yue Wang OmniSep: Unified Omni-Modality Sound Separation with Query-Mixup
Xize Cheng, Siqi Zheng, Zehan Wang, Minghui Fang, Ziang Zhang, Rongjie Huang, Shengpeng Ji, Jialong Zuo, Tao Jin, Zhou Zhao OmnixR: Evaluating Omni-Modality Language Models on Reasoning Across Modalities
Lichang Chen, Hexiang Hu, Mingda Zhang, Yiwen Chen, Zifeng Wang, Yandong Li, Pranav Shyam, Tianyi Zhou, Heng Huang, Ming-Hsuan Yang, Boqing Gong On a Connection Between Imitation Learning and RLHF
Teng Xiao, Yige Yuan, Mingxiao Li, Zhengyu Chen, Vasant G Honavar On Disentangled Training for Nonlinear Transform in Learned Image Compression
Han Li, Shaohui Li, Wenrui Dai, Maida Cao, Nuowen Kan, Chenglin Li, Junni Zou, Hongkai Xiong On Evaluating the Durability of Safeguards for Open-Weight LLMs
Xiangyu Qi, Boyi Wei, Nicholas Carlini, Yangsibo Huang, Tinghao Xie, Luxi He, Matthew Jagielski, Milad Nasr, Prateek Mittal, Peter Henderson On Large Language Model Continual Unlearning
Chongyang Gao, Lixu Wang, Kaize Ding, Chenkai Weng, Xiao Wang, Qi Zhu On Quantizing Neural Representation for Variable-Rate Video Coding
Junqi Shi, Zhujia Chen, Hanfei Li, Qi Zhao, Ming Lu, Tong Chen, Zhan Ma On Rollouts in Model-Based Reinforcement Learning
Bernd Frauenknecht, Devdutt Subhasish, Friedrich Solowjow, Sebastian Trimpe On Scaling up 3D Gaussian Splatting Training
Hexu Zhao, Haoyang Weng, Daohan Lu, Ang Li, Jinyang Li, Aurojit Panda, Saining Xie On Speeding up Language Model Evaluation
Jin Peng Zhou, Christian K Belardi, Ruihan Wu, Travis Zhang, Carla P Gomes, Wen Sun, Kilian Q Weinberger On Targeted Manipulation and Deception When Optimizing LLMs for User Feedback
Marcus Williams, Micah Carroll, Adhyyan Narang, Constantin Weisser, Brendan Murphy, Anca Dragan On the Adversarial Vulnerability of Label-Free Test-Time Adaptation
Shahriar Rifat, Jonathan Ashdown, Michael J. De Lucia, Ananthram Swami, Francesco Restuccia On the Benefits of Attribute-Driven Graph Domain Adaptation
Ruiyi Fang, Bingheng Li, Zhao Kang, Qiuhao Zeng, Nima Hosseini Dashtbayaz, Ruizhi Pu, Boyu Wang, Charles Ling On the Benefits of Memory for Modeling Time-Dependent PDEs
Ricardo Buitrago, Tanya Marwah, Albert Gu, Andrej Risteski On the Expressiveness and Spectral Bias of KANs
Yixuan Wang, Jonathan W. Siegel, Ziming Liu, Thomas Y. Hou On the Identification of Temporal Causal Representation with Instantaneous Dependence
Zijian Li, Yifan Shen, Kaitao Zheng, Ruichu Cai, Xiangchen Song, Mingming Gong, Guangyi Chen, Kun Zhang On the Performance Analysis of Momentum Method: A Frequency Domain Perspective
Xianliang Li, Jun Luo, Zhiwei Zheng, Hanxiao Wang, Li Luo, Lingkun Wen, Linlong Wu, Sheng Xu On the Price of Differential Privacy for Hierarchical Clustering
Chengyuan Deng, Jie Gao, Jalaj Upadhyay, Chen Wang, Samson Zhou On the Role of Attention Heads in Large Language Model Safety
Zhenhong Zhou, Haiyang Yu, Xinghua Zhang, Rongwu Xu, Fei Huang, Kun Wang, Yang Liu, Junfeng Fang, Yongbin Li On the Transfer of Object-Centric Representation Learning
Aniket Rajiv Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael Curtis Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer One Step Diffusion via Shortcut Models
Kevin Frans, Danijar Hafner, Sergey Levine, Pieter Abbeel One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt
Tao Liu, Kai Wang, Senmao Li, Joost van de Weijer, Fahad Shahbaz Khan, Shiqi Yang, Yaxing Wang, Jian Yang, Ming-Ming Cheng Online Clustering with Nearly Optimal Consistency
T-H. Hubert Chan, Shaofeng H.-C. Jiang, Tianyi Wu, Mengshi Zhao Online Reinforcement Learning in Non-Stationary Context-Driven Environments
Pouya Hamadanian, Arash Nasr-Esfahany, Malte Schwarzkopf, Siddhartha Sen, Mohammad Alizadeh Online-to-Offline RL for Agent Alignment
Xu Liu, Haobo Fu, Stefano V Albrecht, Qiang Fu, Shuai Li Open-CK: A Large Multi-Physics Fields Coupling Benchmarks in Combustion Kinetics
Zaige Fei, Fan Xu, Junyuan Mao, Yuxuan Liang, Qingsong Wen, Kun Wang, Hao Wu, Yang Wang Open-Set Graph Anomaly Detection via Normal Structure Regularisation
Qizhou Wang, Guansong Pang, Mahsa Salehi, Xiaokun Xia, Christopher Leckie Open-World Reinforcement Learning over Long Short-Term Imagination
Jiajian Li, Qi Wang, Yunbo Wang, Xin Jin, Yang Li, Wenjun Zeng, Xiaokang Yang Open-YOLO 3D: Towards Fast and Accurate Open-Vocabulary 3D Instance Segmentation
Mohamed El Amine Boudjoghra, Angela Dai, Jean Lahoud, Hisham Cholakkal, Rao Muhammad Anwer, Salman Khan, Fahad Shahbaz Khan OpenHands: An Open Platform for AI Software Developers as Generalist Agents
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Shubham Toshniwal, Wei Du, Ivan Moshkov, Branislav Kisacanin, Alexan Ayrapetyan, Igor Gitman OpenPRM: Building Open-Domain Process-Based Reward Models with Preference Trees
Kaiyan Zhang, Jiayuan Zhang, Haoxin Li, Xuekai Zhu, Ermo Hua, Xingtai Lv, Ning Ding, Biqing Qi, Bowen Zhou OpenRCA: Can Large Language Models Locate the Root Cause of Software Failures?
Junjielong Xu, Qinan Zhang, Zhiqing Zhong, Shilin He, Chaoyun Zhang, Qingwei Lin, Dan Pei, Pinjia He, Dongmei Zhang, Qi Zhang OpenVid-1m: A Large-Scale High-Quality Dataset for Text-to-Video Generation
Kepan Nan, Rui Xie, Penghao Zhou, Tiehan Fan, Zhenheng Yang, Zhijie Chen, Xiang Li, Jian Yang, Ying Tai Operator Deep Smoothing for Implied Volatility
Ruben Wiedemann, Antoine Jacquier, Lukas Gonon OPTAMI: Global Superlinear Convergence of High-Order Methods
Dmitry Kamzolov, Artem Agafonov, Dmitry Pasechnyuk, Alexander Gasnikov, Martin Takáč OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling
Zhicheng Yang, Yiwei Wang, Yinya Huang, Zhijiang Guo, Wei Shi, Xiongwei Han, Liang Feng, Linqi Song, Xiaodan Liang, Jing Tang Optimal Brain Apoptosis
Mingyuan Sun, Zheng Fang, Jiaxu Wang, Junjie Jiang, Delei Kong, Chenming Hu, Yuetong Fang, Renjing Xu Optimal Transport for Time Series Imputation
Hao Wang, Zhengnan Li, Haoxuan Li, Xu Chen, Mingming Gong, BinChen, Zhichao Chen Optimizing $(l_0, L_1)$-Smooth Functions by Gradient Methods
Daniil Vankov, Anton Rodomanov, Angelia Nedich, Lalitha Sankar, Sebastian U Stich Optimizing 4D Gaussians for Dynamic Scene Video from Single Landscape Images
In-Hwan Jin, Haesoo Choo, Seong-Hun Jeong, Park Heemoon, Junghwan Kim, Oh-joon Kwon, Kyeongbo Kong Optimizing Neural Network Representations of Boolean Networks
Joshua Russell, Ignacio Gavier, Devdhar Patel, Edward Rietman, Hava T Siegelmann OptionZero: Planning with Learned Options
Po-Wei Huang, Pei-Chiun Peng, Hung Guei, Ti-Rong Wu Oracle Efficient Truncated Statistics
Konstantinos Karatapanis, Vasilis Kontonis, Christos Tzamos Order-Aware Interactive Segmentation
Bin Wang, Anwesa Choudhuri, Meng Zheng, Zhongpai Gao, Benjamin Planche, Andong Deng, Qin Liu, Terrence Chen, Ulas Bagci, Ziyan Wu OS-ATLAS: Foundation Action Model for Generalist GUI Agents
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T. Konstantin Rusch, Daniela Rus OvercookedV2: Rethinking Overcooked for Zero-Shot Coordination
Tobias Gessler, Tin Dizdarevic, Ani Calinescu, Benjamin Ellis, Andrei Lupu, Jakob Nicolaus Foerster PABBO: Preferential Amortized Black-Box Optimization
Xinyu Zhang, Daolang Huang, Samuel Kaski, Julien Martinelli PaCA: Partial Connection Adaptation for Efficient Fine-Tuning
Sunghyeon Woo, Sol Namkung, Sunwoo Lee, Inho Jeong, Beomseok Kim, Dongsuk Jeon PAD: Personalized Alignment of LLMs at Decoding-Time
Ruizhe Chen, Xiaotian Zhang, Meng Luo, Wenhao Chai, Zuozhu Liu PADRe: A Unifying Polynomial Attention Drop-in Replacement for Efficient Vision Transformer
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Yilong Li, Jingyu Liu, Hao Zhang, M Badri Narayanan, Utkarsh Sharma, Shuai Zhang, Yijing Zeng, Jayaram Raghuram, Suman Banerjee Palu: KV-Cache Compression with Low-Rank Projection
Chi-Chih Chang, Wei-Cheng Lin, Chien-Yu Lin, Chong-Yan Chen, Yu-Fang Hu, Pei-Shuo Wang, Ning-Chi Huang, Luis Ceze, Mohamed S. Abdelfattah, Kai-Chiang Wu Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages
Xiang Yue, Yueqi Song, Akari Asai, Seungone Kim, Jean de Dieu Nyandwi, Simran Khanuja, Anjali Kantharuban, Lintang Sutawika, Sathyanarayanan Ramamoorthy, Graham Neubig PaPaGei: Open Foundation Models for Optical Physiological Signals
Arvind Pillai, Dimitris Spathis, Fahim Kawsar, Mohammad Malekzadeh Pareto Prompt Optimization
Guang Zhao, Byung-Jun Yoon, Gilchan Park, Shantenu Jha, Shinjae Yoo, Xiaoning Qian Partial Gromov-Wasserstein Metric
Yikun Bai, Rocio Diaz Martin, Abihith Kothapalli, Hengrong Du, Xinran Liu, Soheil Kolouri PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-Agent Tasks
Matthew Chang, Gunjan Chhablani, Alexander Clegg, Mikael Dallaire Cote, Ruta Desai, Michal Hlavac, Vladimir Karashchuk, Jacob Krantz, Roozbeh Mottaghi, Priyam Parashar, Siddharth Patki, Ishita Prasad, Xavier Puig, Akshara Rai, Ram Ramrakhya, Daniel Tran, Joanne Truong, John M Turner, Eric Undersander, Tsung-Yen Yang PathGen-1.6m: 1.6 Million Pathology Image-Text Pairs Generation Through Multi-Agent Collaboration
Yuxuan Sun, Yunlong Zhang, Yixuan Si, Chenglu Zhu, Kai Zhang, Zhongyi Shui, Jingxiong Li, Xuan Gong, Xinheng Lyu, Tao Lin, Lin Yang PEARL: Parallel Speculative Decoding with Adaptive Draft Length
Tianyu Liu, Yun Li, Qitan Lv, Kai Liu, Jianchen Zhu, Winston Hu, Xiao Sun PEARL: Towards Permutation-Resilient LLMs
Liang Chen, Li Shen, Yang Deng, Xiaoyan Zhao, Bin Liang, Kam-Fai Wong Pedestrian Motion Reconstruction: A Large-Scale Benchmark via Mixed Reality Rendering with Multiple Perspectives and Modalities
Yichen Wang, Yiyi Zhang, Xinhao Hu, Li Niu, Jianfu Zhang, Yasushi Makihara, Yasushi Yagi, Pai Peng, Wenlong Liao, Tao He, Junchi Yan, Liqing Zhang Periodic Materials Generation Using Text-Guided Joint Diffusion Model
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Chengan He, Xin Sun, Zhixin Shu, Fujun Luan, Soren Pirk, Jorge Alejandro Amador Herrera, Dominik Michels, Tuanfeng Yang Wang, Meng Zhang, Holly Rushmeier, Yi Zhou Perplexed by Perplexity: Perplexity-Based Data Pruning with Small Reference Models
Zachary Ankner, Cody Blakeney, Kartik Sreenivasan, Max Marion, Matthew L Leavitt, Mansheej Paul Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents
Haoyu Wang, Sunhao Dai, Haiyuan Zhao, Liang Pang, Xiao Zhang, Gang Wang, Zhenhua Dong, Jun Xu, Ji-Rong Wen Persistent Pre-Training Poisoning of LLMs
Yiming Zhang, Javier Rando, Ivan Evtimov, Jianfeng Chi, Eric Michael Smith, Nicholas Carlini, Florian Tramèr, Daphne Ippolito Personality Alignment of Large Language Models
Minjun Zhu, Yixuan Weng, Linyi Yang, Yue Zhang Personalized Representation from Personalized Generation
Shobhita Sundaram, Julia Chae, Yonglong Tian, Sara Beery, Phillip Isola Personalized Visual Instruction Tuning
Renjie Pi, Jianshu Zhang, Tianyang Han, Jipeng Zhang, Rui Pan, Tong Zhang PersonalLLM: Tailoring LLMs to Individual Preferences
Thomas P Zollo, Andrew Wei Tung Siah, Naimeng Ye, Ang Li, Hongseok Namkoong Perturbation-Restrained Sequential Model Editing
Jun-Yu Ma, Hong Wang, Hao-Xiang Xu, Zhen-Hua Ling, Jia-Chen Gu PerturboLLaVA: Reducing Multimodal Hallucinations with Perturbative Visual Training
Cong Chen, Mingyu Liu, Chenchen Jing, Yizhou Zhou, Fengyun Rao, Hao Chen, Bo Zhang, Chunhua Shen PETRA: Parallel End-to-End Training with Reversible Architectures
Stephane Rivaud, Louis Fournier, Thomas Pumir, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon PhyMPGN: Physics-Encoded Message Passing Graph Network for Spatiotemporal PDE Systems
Bocheng Zeng, Qi Wang, Mengtao Yan, Yang Liu, Ruizhi Chengze, Yi Zhang, Hongsheng Liu, Zidong Wang, Hao Sun Physics-Aligned Field Reconstruction with Diffusion Bridge
Zeyu Li, Hongkun Dou, Shen Fang, Wang Han, Yue Deng, Lijun Yang Physics-Informed Diffusion Models
Jan-Hendrik Bastek, WaiChing Sun, Dennis Kochmann Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time-Series Forecasting Based on Biological ODEs
Christian Klötergens, Vijaya Krishna Yalavarthi, Randolf Scholz, Maximilian Stubbemann, Stefan Born, Lars Schmidt-Thieme PICASO: Permutation-Invariant Context Composition with State Space Models
Tian Yu Liu, Alessandro Achille, Matthew Trager, Aditya Golatkar, Luca Zancato, Stefano Soatto PiCO: Peer Review in LLMs Based on Consistency Optimization
Kun-Peng Ning, Shuo Yang, Yuyang Liu, Jia-Yu Yao, Zhenhui Liu, Yonghong Tian, Yibing Song, Li Yuan PIED: Physics-Informed Experimental Design for Inverse Problems
Apivich Hemachandra, Gregory Kang Ruey Lau, See-Kiong Ng, Bryan Kian Hsiang Low PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructions
Weifeng Lin, Xinyu Wei, Renrui Zhang, Le Zhuo, Shitian Zhao, Siyuan Huang, Junlin Xie, Peng Gao, Hongsheng Li Planning in Natural Language Improves LLM Search for Code Generation
Evan Z Wang, Federico Cassano, Catherine Wu, Yunfeng Bai, William Song, Vaskar Nath, Ziwen Han, Sean M. Hendryx, Summer Yue, Hugh Zhang Plastic Learning with Deep Fourier Features
Alex Lewandowski, Dale Schuurmans, Marlos C. Machado PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
Ségolène Tiffany Martin, Anne Gagneux, Paul Hagemann, Gabriele Steidl POGEMA: A Benchmark Platform for Cooperative Multi-Agent Pathfinding
Alexey Skrynnik, Anton Andreychuk, Anatolii Borzilov, Alexander Chernyavskiy, Konstantin Yakovlev, Aleksandr Panov Point Cluster: A Compact Message Unit for Communication-Efficient Collaborative Perception
Zihan Ding, Jiahui Fu, Si Liu, Hongyu Li, Siheng Chen, Hongsheng Li, Shifeng Zhang, Xu Zhou Point-SAM: Promptable 3D Segmentation Model for Point Clouds
Yuchen Zhou, Jiayuan Gu, Tung Yen Chiang, Fanbo Xiang, Hao Su Poison-Splat: Computation Cost Attack on 3D Gaussian Splatting
Jiahao Lu, Yifan Zhang, Qiuhong Shen, Xinchao Wang, Shuicheng Yan Policy Design in Long-Run Welfare Dynamics
Jiduan Wu, Rediet Abebe, Moritz Hardt, Ana-Andreea Stoica PolyPythias: Stability and Outliers Across Fifty Language Model Pre-Training Runs
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Geeling Chau, Christopher Wang, Sabera J Talukder, Vighnesh Subramaniam, Saraswati Soedarmadji, Yisong Yue, Boris Katz, Andrei Barbu Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation
Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Yuuki Yamanaka, Tomoya Yamashita Post-Hoc Reward Calibration: A Case Study on Length Bias
Zeyu Huang, Zihan Qiu, Zili Wang, Edoardo Ponti, Ivan Titov PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling
Junchao Gong, Siwei Tu, Weidong Yang, Ben Fei, Kun Chen, Zhangwenlong, Xiaokang Yang, Wanli Ouyang, Lei Bai PostEdit: Posterior Sampling for Efficient Zero-Shot Image Editing
Feng Tian, Yixuan Li, Yichao Yan, Shanyan Guan, Yanhao Ge, Xiaokang Yang PQMass: Probabilistic Assessment of the Quality of Generative Models Using Probability Mass Estimation
Pablo Lemos, Sammy Nasser Sharief, Nikolay Malkin, Salma Salhi, Connor Stone, Laurence Perreault-Levasseur, Yashar Hezaveh Preble: Efficient Distributed Prompt Scheduling for LLM Serving
Vikranth Srivatsa, Zijian He, Reyna Abhyankar, Dongming Li, Yiying Zhang Precise Parameter Localization for Textual Generation in Diffusion Models
Łukasz Staniszewski, Bartosz Cywiński, Franziska Boenisch, Kamil Deja, Adam Dziedzic Preference Diffusion for Recommendation
Shuo Liu, An Zhang, Guoqing Hu, Hong Qian, Tat-Seng Chua Preference Elicitation for Offline Reinforcement Learning
Alizée Pace, Bernhard Schölkopf, Gunnar Ratsch, Giorgia Ramponi Preference Optimization for Reasoning with Pseudo Feedback
Fangkai Jiao, Geyang Guo, Xingxing Zhang, Nancy F. Chen, Shafiq Joty, Furu Wei Preserving Diversity in Supervised Fine-Tuning of Large Language Models
Ziniu Li, Congliang Chen, Tian Xu, Zeyu Qin, Jiancong Xiao, Zhi-Quan Luo, Ruoyu Sun Presto! Distilling Steps and Layers for Accelerating Music Generation
Zachary Novack, Ge Zhu, Jonah Casebeer, Julian McAuley, Taylor Berg-Kirkpatrick, Nicholas J. Bryan Prioritized Generative Replay
Renhao Wang, Kevin Frans, Pieter Abbeel, Sergey Levine, Alexei A Efros Privacy Auditing of Large Language Models
Ashwinee Panda, Xinyu Tang, Christopher A. Choquette-Choo, Milad Nasr, Prateek Mittal Privacy-Aware Lifelong Learning
Ozan Ozdenizci, Elmar Rueckert, Robert Legenstein Private Mechanism Design via Quantile Estimation
Yuanyuan Yang, Tao Xiao, Bhuvesh Kumar, Jamie Heather Morgenstern Privately Counting Partially Ordered Data
Matthew Joseph, Mónica Ribero, Alexander Yu Proactive Agent: Shifting LLM Agents from Reactive Responses to Active Assistance
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Martin Kuo, Jingyang Zhang, Jianyi Zhang, Minxue Tang, Louis DiValentin, Aolin Ding, Jingwei Sun, William Chen, Amin Hass, Tianlong Chen, Yiran Chen, Hai Li ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs
Hao Di, Tong He, Haishan Ye, Yinghui Huang, Xiangyu Chang, Guang Dai, Ivor Tsang Probabilistic Conformal Prediction with Approximate Conditional Validity
Vincent Plassier, Alexander Fishkov, Mohsen Guizani, Maxim Panov, Eric Moulines Probabilistic Language-Image Pre-Training
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Antonio Sclocchi, Alessandro Favero, Noam Itzhak Levi, Matthieu Wyart Problem-Parameter-Free Federated Learning
Wenjing Yan, Kai Zhang, Xiaolu Wang, Xuanyu Cao Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models
Laura Ruis, Maximilian Mozes, Juhan Bae, Siddhartha Rao Kamalakara, Dwaraknath Gnaneshwar, Acyr Locatelli, Robert Kirk, Tim Rocktäschel, Edward Grefenstette, Max Bartolo Procedural Synthesis of Synthesizable Molecules
Michael Sun, Alston Lo, Minghao Guo, Jie Chen, Connor W. Coley, Wojciech Matusik Programming Refusal with Conditional Activation Steering
Bruce W. Lee, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Erik Miehling, Pierre Dognin, Manish Nagireddy, Amit Dhurandhar Progressive Distillation Induces an Implicit Curriculum
Abhishek Panigrahi, Bingbin Liu, Sadhika Malladi, Andrej Risteski, Surbhi Goel Progressive Mixed-Precision Decoding for Efficient LLM Inference
Hao Mark Chen, Fuwen Tan, Alexandros Kouris, Royson Lee, Hongxiang Fan, Stylianos Venieris Projection Head Is Secretly an Information Bottleneck
Zhuo Ouyang, Kaiwen Hu, Qi Zhang, Yifei Wang, Yisen Wang Prompting Fairness: Integrating Causality to Debias Large Language Models
Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu Promptriever: Instruction-Trained Retrievers Can Be Prompted like Language Models
Orion Weller, Benjamin Van Durme, Dawn Lawrie, Ashwin Paranjape, Yuhao Zhang, Jack Hessel ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids
Hannes Stark, Bowen Jing, Tomas Geffner, Jason Yim, Tommi Jaakkola, Arash Vahdat, Karsten Kreis Protecting Against Simultaneous Data Poisoning Attacks
Neel Alex, Shoaib Ahmed Siddiqui, Amartya Sanyal, David Krueger Proteina: Scaling Flow-Based Protein Structure Generative Models
Tomas Geffner, Kieran Didi, Zuobai Zhang, Danny Reidenbach, Zhonglin Cao, Jason Yim, Mario Geiger, Christian Dallago, Emine Kucukbenli, Arash Vahdat, Karsten Kreis ProteinBench: A Holistic Evaluation of Protein Foundation Models
Fei Ye, Zaixiang Zheng, Dongyu Xue, Yuning Shen, Lihao Wang, Yiming Ma, Yan Wang, Xinyou Wang, Xiangxin Zhou, Quanquan Gu ProtoSnap: Prototype Alignment for Cuneiform Signs
Rachel Mikulinsky, Morris Alper, Shai Gordin, Enrique Jiménez, Yoram Cohen, Hadar Averbuch-Elor Provable Uncertainty Decomposition via Higher-Order Calibration
Gustaf Ahdritz, Aravind Gollakota, Parikshit Gopalan, Charlotte Peale, Udi Wieder Provable Unlearning in Topic Modeling and Downstream Tasks
Stanley Wei, Sadhika Malladi, Sanjeev Arora, Amartya Sanyal Provably Safeguarding a Classifier from OOD and Adversarial Samples
Nicolas Atienza, Johanne Cohen, Christophe Labreuche, Michele Sebag Proving Olympiad Inequalities by Synergizing LLMs and Symbolic Reasoning
Zenan Li, Zhaoyu Li, Wen Tang, Xian Zhang, Yuan Yao, Xujie Si, Fan Yang, Kaiyu Yang, Xiaoxing Ma Proxy Denoising for Source-Free Domain Adaptation
Song Tang, Wenxin Su, Yan Gan, Mao Ye, Jianwei Dr. Zhang, Xiatian Zhu PseDet: Revisiting the Power of Pseudo Label in Incremental Object Detection
Qiuchen Wang, Zehui Chen, Chenhongyi Yang, Jiaming Liu, Zhenyu Li, Feng Zhao PWM: Policy Learning with Multi-Task World Models
Ignat Georgiev, Varun Giridhar, Nicklas Hansen, Animesh Garg Pyramidal Flow Matching for Efficient Video Generative Modeling
Yang Jin, Zhicheng Sun, Ningyuan Li, Kun Xu, Kun Xu, Hao Jiang, Nan Zhuang, Quzhe Huang, Yang Song, Yadong Mu, Zhouchen Lin Q-Adapter: Customizing Pre-Trained LLMs to New Preferences with Forgetting Mitigation
Yi-Chen Li, Fuxiang Zhang, Wenjie Qiu, Lei Yuan, Chengxing Jia, Zongzhang Zhang, Yang Yu, Bo An QA-Calibration of Language Model Confidence Scores
Putra Manggala, Atalanti A. Mastakouri, Elke Kirschbaum, Shiva Kasiviswanathan, Aaditya Ramdas QERA: An Analytical Framework for Quantization Error Reconstruction
Cheng Zhang, Jeffrey T. H. Wong, Can Xiao, George Anthony Constantinides, Yiren Zhao QMP: Q-Switch Mixture of Policies for Multi-Task Behavior Sharing
Grace Zhang, Ayush Jain, Injune Hwang, Shao-Hua Sun, Joseph J Lim qNBO: Quasi-Newton Meets Bilevel Optimization
Sheng Fang, Yongjin Liu, Wei Yao, Chengming Yu, Jin Zhang QP-SNN: Quantized and Pruned Spiking Neural Networks
Wenjie Wei, Malu Zhang, Zijian Zhou, Ammar Belatreche, Yimeng Shan, Yu Liang, Honglin Cao, Jieyuan Zhang, Yang Yang QPM: Discrete Optimization for Globally Interpretable Image Classification
Thomas Norrenbrock, Timo Kaiser, Sovan Biswas, Ramesh Manuvinakurike, Bodo Rosenhahn Quality Measures for Dynamic Graph Generative Models
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Xinze Li, Sen Mei, Zhenghao Liu, Yukun Yan, Shuo Wang, Shi Yu, Zheni Zeng, Hao Chen, Ge Yu, Zhiyuan Liu, Maosong Sun, Chenyan Xiong RainbowPO: A Unified Framework for Combining Improvements in Preference Optimization
Hanyang Zhao, Genta Indra Winata, Anirban Das, Shi-Xiong Zhang, David Yao, Wenpin Tang, Sambit Sahu RandLoRA: Full Rank Parameter-Efficient Fine-Tuning of Large Models
Paul Albert, Frederic Z. Zhang, Hemanth Saratchandran, Cristian Rodriguez-Opazo, Anton van den Hengel, Ehsan Abbasnejad Random-Set Neural Networks
Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Keivan Shariatmadar, Fabio Cuzzolin Range, Not Independence, Drives Modularity in Biologically Inspired Representations
Will Dorrell, Kyle Hsu, Luke Hollingsworth, Jin Hwa Lee, Jiajun Wu, Chelsea Finn, Peter E. Latham, Timothy Edward John Behrens, James C. R. Whittington Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning
Patrick Yin, Tyler Westenbroek, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta RaSA: Rank-Sharing Low-Rank Adaptation
Zhiwei He, Zhaopeng Tu, Xing Wang, Xingyu Chen, Zhijie Wang, Jiahao Xu, Tian Liang, Wenxiang Jiao, Zhuosheng Zhang, Rui Wang Rational Decision-Making Agent with Learning Internal Utility Judgment
Yining Ye, Xin Cong, Shizuo Tian, Yujia Qin, Chong Liu, Yankai Lin, Zhiyuan Liu, Maosong Sun Rationalizing and Augmenting Dynamic Graph Neural Networks
Guibin Zhang, Yiyan Qi, Ziyang Cheng, Yanwei Yue, Dawei Cheng, Jian Guo RazorAttention: Efficient KV Cache Compression Through Retrieval Heads
Hanlin Tang, Yang Lin, Jing Lin, Qingsen Han, Danning Ke, Shikuan Hong, Yiwu Yao, Gongyi Wang RB-Modulation: Training-Free Stylization Using Reference-Based Modulation
Litu Rout, Yujia Chen, Nataniel Ruiz, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu RDT-1B: A Diffusion Foundation Model for Bimanual Manipulation
Songming Liu, Lingxuan Wu, Bangguo Li, Hengkai Tan, Huayu Chen, Zhengyi Wang, Ke Xu, Hang Su, Jun Zhu Re-Aligning Language to Visual Objects with an Agentic Workflow
Yuming Chen, Jiangyan Feng, Haodong Zhang, Lijun Gong, Feng Zhu, Rui Zhao, Qibin Hou, Ming-Ming Cheng, Yibing Song Re-Evaluating Open-Ended Evaluation of Large Language Models
Siqi Liu, Ian Gemp, Luke Marris, Georgios Piliouras, Nicolas Heess, Marc Lanctot Re-Imagining Multimodal Instruction Tuning: A Representation View
Yiyang Liu, James Chenhao Liang, Ruixiang Tang, Yugyung Lee, Majid Rabbani, Sohail Dianat, Raghuveer Rao, Lifu Huang, Dongfang Liu, Qifan Wang, Cheng Han Ready-to-React: Online Reaction Policy for Two-Character Interaction Generation
Zhi Cen, Huaijin Pi, Sida Peng, Qing Shuai, Yujun Shen, Hujun Bao, Xiaowei Zhou, Ruizhen Hu Realistic Evaluation of Deep Partial-Label Learning Algorithms
Wei Wang, Dong-Dong Wu, Jindong Wang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama Reasoning Elicitation in Language Models via Counterfactual Feedback
Alihan Hüyük, Xinnuo Xu, Jacqueline R. M. A. Maasch, Aditya V. Nori, Javier Gonzalez Reasoning with Latent Thoughts: On the Power of Looped Transformers
Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li, Sanjiv Kumar, Sashank J. Reddi Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval
Pengcheng Jiang, Cao Xiao, Minhao Jiang, Parminder Bhatia, Taha Kass-Hout, Jimeng Sun, Jiawei Han ReAttention: Training-Free Infinite Context with Finite Attention Scope
Xiaoran Liu, Ruixiao Li, Zhigeng Liu, Qipeng Guo, Yuerong Song, Kai Lv, Hang Yan, Linlin Li, Qun Liu, Xipeng Qiu RecDreamer: Consistent Text-to-3D Generation via Uniform Score Distillation
Chenxi Zheng, Yihong Lin, Bangzhen Liu, Xuemiao Xu, Yongwei Nie, Shengfeng He RecFlow: An Industrial Full Flow Recommendation Dataset
Qi Liu, Kai Zheng, Rui Huang, Wuchao Li, Kuo Cai, Yuan Chai, Yanan Niu, Yiqun Hui, Bing Han, Na Mou, Hongning Wang, Wentian Bao, Enyun Yu, Guorui Zhou, Han Li, Yang Song, Defu Lian, Kun Gai Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon
USVSN Sai Prashanth, Alvin Deng, Kyle O'Brien, S V Jyothir, Mohammad Aflah Khan, Jaydeep Borkar, Christopher A. Choquette-Choo, Jacob Ray Fuehne, Stella Biderman, Tracy Ke, Katherine Lee, Naomi Saphra ReCogLab: A Framework Testing Relational Reasoning & Cognitive Hypotheses on LLMs
Andrew Liu, Henry Prior, Gargi Balasubramaniam, Rivka Moroshko, Amir Zait, Ilia Labzovsky, Danny Karmon, Ishita Dasgupta, Kim Stachenfeld, Kenneth Marino Recognize Any Surgical Object: Unleashing the Power of Weakly-Supervised Data
Jiajie Li, Brian R Quaranto, Chenhui Xu, Ishan Mishra, Ruiyang Qin, Dancheng Liu, Peter C W Kim, Jinjun Xiong Reconstructive Visual Instruction Tuning
Haochen Wang, Anlin Zheng, Yucheng Zhao, Tiancai Wang, Zheng Ge, Xiangyu Zhang, Zhaoxiang Zhang Redefining the Task of Bioactivity Prediction
Yanwen Huang, Bowen Gao, Yinjun Jia, Hongbo Ma, Wei-Ying Ma, Ya-Qin Zhang, Yanyan Lan REEF: Representation Encoding Fingerprints for Large Language Models
Jie Zhang, Dongrui Liu, Chen Qian, Linfeng Zhang, Yong Liu, Yu Qiao, Jing Shao RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code
Dhruv Gautam, Spandan Garg, Jinu Jang, Neel Sundaresan, Roshanak Zilouchian Moghaddam Refine Knowledge of Large Language Models via Adaptive Contrastive Learning
Yinghui Li, Haojing Huang, Jiayi Kuang, Yangning Li, Shu-Yu Guo, Chao Qu, Xiaoyu Tan, Hai-Tao Zheng, Ying Shen, Philip S. Yu Refine-by-Align: Reference-Guided Artifacts Refinement Through Semantic Alignment
Yizhi Song, Liu He, Zhifei Zhang, Soo Ye Kim, He Zhang, Wei Xiong, Zhe Lin, Brian L. Price, Scott Cohen, Jianming Zhang, Daniel Aliaga REFINE: Inversion-Free Backdoor Defense via Model Reprogramming
Yukun Chen, Shuo Shao, Enhao Huang, Yiming Li, Pin-Yu Chen, Zhan Qin, Kui Ren Reflective Gaussian Splatting
Yuxuan Yao, Zixuan Zeng, Chun Gu, Xiatian Zhu, Li Zhang Reframing Structure-Based Drug Design Model Evaluation via Metrics Correlated to Practical Needs
Bowen Gao, Haichuan Tan, Yanwen Huang, Minsi Ren, Xiao Huang, Wei-Ying Ma, Ya-Qin Zhang, Yanyan Lan ReGen: Generative Robot Simulation via Inverse Design
Phat Tan Nguyen, Tsun-Hsuan Wang, Zhang-Wei Hong, Erfan Aasi, Andrew Silva, Guy Rosman, Sertac Karaman, Daniela Rus ReGenesis: LLMs Can Grow into Reasoning Generalists via Self-Improvement
Xiangyu Peng, Congying Xia, Xinyi Yang, Caiming Xiong, Chien-Sheng Wu, Chen Xing RegMix: Data Mixture as Regression for Language Model Pre-Training
Qian Liu, Xiaosen Zheng, Niklas Muennighoff, Guangtao Zeng, Longxu Dou, Tianyu Pang, Jing Jiang, Min Lin Regressing the Relative Future: Efficient Policy Optimization for Multi-Turn RLHF
Zhaolin Gao, Wenhao Zhan, Jonathan Daniel Chang, Gokul Swamy, Kianté Brantley, Jason D. Lee, Wen Sun Regretful Decisions Under Label Noise
Sujay Nagaraj, Yang Liu, Flavio Calmon, Berk Ustun Regularization by Texts for Latent Diffusion Inverse Solvers
Jeongsol Kim, Geon Yeong Park, Hyungjin Chung, Jong Chul Ye Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards
Zhaohui Jiang, Xuening Feng, Paul Weng, Yifei Zhu, Yan Song, Tianze Zhou, Yujing Hu, Tangjie Lv, Changjie Fan Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-Wise LoRA
Sangmin Bae, Adam Fisch, Hrayr Harutyunyan, Ziwei Ji, Seungyeon Kim, Tal Schuster RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable Data
Maxwell A Xu, Jaya Narain, Gregory Darnell, Haraldur T Hallgrimsson, Hyewon Jeong, Darren Forde, Richard Andres Fineman, Karthik Jayaraman Raghuram, James Matthew Rehg, Shirley You Ren RelitLRM: Generative Relightable Radiance for Large Reconstruction Models
Tianyuan Zhang, Zhengfei Kuang, Haian Jin, Zexiang Xu, Sai Bi, Hao Tan, He Zhang, Yiwei Hu, Milos Hasan, William T. Freeman, Kai Zhang, Fujun Luan ReMatching Dynamic Reconstruction Flow
Sara Oblak, Despoina Paschalidou, Sanja Fidler, Matan Atzmon REMEDY: Recipe Merging Dynamics in Large Vision-Language Models
Didi Zhu, Yibing Song, Tao Shen, Ziyu Zhao, Jinluan Yang, Min Zhang, Chao Wu ReNovo: Retrieval-Based \emph{De Novo} Mass Spectrometry Peptide Sequencing
Shaorong Chen, Jun Xia, Jingbo Zhou, Lecheng Zhang, Zhangyang Gao, Bozhen Hu, Cheng Tan, Wenjie Du, Stan Z. Li Repetition Improves Language Model Embeddings
Jacob Mitchell Springer, Suhas Kotha, Daniel Fried, Graham Neubig, Aditi Raghunathan RepoGraph: Enhancing AI Software Engineering with Repository-Level Code Graph
Siru Ouyang, Wenhao Yu, Kaixin Ma, Zilin Xiao, Zhihan Zhang, Mengzhao Jia, Jiawei Han, Hongming Zhang, Dong Yu Representation Alignment for Generation: Training Diffusion Transformers Is Easier than You Think
Sihyun Yu, Sangkyung Kwak, Huiwon Jang, Jongheon Jeong, Jonathan Huang, Jinwoo Shin, Saining Xie RESfM: Robust Deep Equivariant Structure from Motion
Fadi Khatib, Yoni Kasten, Dror Moran, Meirav Galun, Ronen Basri ReSi: A Comprehensive Benchmark for Representational Similarity Measures
Max Klabunde, Tassilo Wald, Tobias Schumacher, Klaus Maier-Hein, Markus Strohmaier, Florian Lemmerich Residual Deep Gaussian Processes on Manifolds
Kacper Wyrwal, Andreas Krause, Viacheslav Borovitskiy Residual Stream Analysis with Multi-Layer SAEs
Tim Lawson, Lucy Farnik, Conor Houghton, Laurence Aitchison Residual-MPPI: Online Policy Customization for Continuous Control
Pengcheng Wang, Chenran Li, Catherine Weaver, Kenta Kawamoto, Masayoshi Tomizuka, Chen Tang, Wei Zhan Restructuring Vector Quantization with the Rotation Trick
Christopher Fifty, Ronald Guenther Junkins, Dennis Duan, Aniketh Iyengar, Jerry Weihong Liu, Ehsan Amid, Sebastian Thrun, Christopher Re Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi, Alasdair Newson, Florence d'Alché-Buc Rethinking Artistic Copyright Infringements in the Era of Text-to-Image Generative Models
Mazda Moayeri, Sriram Balasubramanian, Samyadeep Basu, Priyatham Kattakinda, Atoosa Chegini, Robert Brauneis, Soheil Feizi Rethinking Classifier Re-Training in Long-Tailed Recognition: Label Over-Smooth Can Balance
Siyu Sun, Han Lu, Jiangtong Li, Yichen Xie, Tianjiao Li, Xiaokang Yang, Liqing Zhang, Junchi Yan Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior
Tongda Xu, Xiyan Cai, Xinjie Zhang, Xingtong Ge, Dailan He, Ming Sun, Jingjing Liu, Ya-Qin Zhang, Jian Li, Yan Wang Rethinking Fair Representation Learning for Performance-Sensitive Tasks
Charles Jones, Fabio De Sousa Ribeiro, Mélanie Roschewitz, Daniel C. Castro, Ben Glocker Rethinking Invariance in In-Context Learning
Lizhe Fang, Yifei Wang, Khashayar Gatmiry, Lei Fang, Yisen Wang Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond
Qizhou Wang, Jin Peng Zhou, Zhanke Zhou, Saebyeol Shin, Bo Han, Kilian Q Weinberger Rethinking Multiple-Instance Learning from Feature Space to Probability Space
Zhaolong Du, Shasha Mao, Xuequan Lu, Mengnan Qi, Yimeng Zhang, Jing Gu, Licheng Jiao Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding
Jinbiao Chen, Zhiguang Cao, Jiahai Wang, Yaoxin Wu, Hanzhang Qin, Zizhen Zhang, Yue-Jiao Gong Rethinking Reward Model Evaluation: Are We Barking up the Wrong Tree?
Xueru Wen, Jie Lou, Yaojie Lu, Hongyu Lin, XingYu, Xinyu Lu, Ben He, Xianpei Han, Debing Zhang, Le Sun Rethinking Visual Counterfactual Explanations Through Region Constraint
Bartlomiej Sobieski, Jakub Grzywaczewski, Bartłomiej Sadlej, Matthew Tivnan, Przemyslaw Biecek Reti-Diff: Illumination Degradation Image Restoration with Retinex-Based Latent Diffusion Model
Chunming He, Chengyu Fang, Yulun Zhang, Longxiang Tang, Jinfa Huang, Kai Li, Zhenhua Guo, Xiu Li, Sina Farsiu Retri3D: 3D Neural Graphics Representation Retrieval
Yushi Guan, Daniel Kwan, Jean Sebastien Dandurand, Xi Yan, Ruofan Liang, Yuxuan Zhang, Nilesh Jain, Nilesh Ahuja, Selvakumar Panneer, Nandita Vijaykumar Revealing and Mitigating Over-Attention in Knowledge Editing
Pinzheng Wang, Zecheng Tang, Keyan Zhou, Juntao Li, Qiaoming Zhu, Min Zhang Revealing the 3D Cosmic Web Through Gravitationally Constrained Neural Fields
Brandon Zhao, Aviad Levis, Liam Connor, Pratul P. Srinivasan, Katherine Bouman RevisEval: Improving LLM-as-a-Judge via Response-Adapted References
Qiyuan Zhang, Yufei Wang, Tiezheng Yu, Yuxin Jiang, Chuhan Wu, Liangyou Li, Yasheng Wang, Xin Jiang, Lifeng Shang, Ruiming Tang, Fuyuan Lyu, Chen Ma Revisit Large-Scale Image-Caption Data in Pre-Training Multimodal Foundation Models
Zhengfeng Lai, Vasileios Saveris, Chen Chen, Hong-You Chen, Haotian Zhang, Bowen Zhang, Wenze Hu, Juan Lao Tebar, Zhe Gan, Peter Grasch, Meng Cao, Yinfei Yang Revisiting Convolution Architecture in the Realm of DNA Foundation Models
Yu Bo, Weian Mao, Yanjun Shao, Weiqiang Bai, Peng Ye, Xinzhu Ma, Junbo Zhao, Hao Chen, Chunhua Shen Revisiting Large-Scale Non-Convex Distributionally Robust Optimization
Qi Zhang, Yi Zhou, Simon Khan, Ashley Prater-Bennette, Lixin Shen, Shaofeng Zou Revisiting Random Walks for Learning on Graphs
Jinwoo Kim, Olga Zaghen, Ayhan Suleymanzade, Youngmin Ryou, Seunghoon Hong Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Rating
Olivia Wiles, Chuhan Zhang, Isabela Albuquerque, Ivana Kajic, Su Wang, Emanuele Bugliarello, Yasumasa Onoe, Pinelopi Papalampidi, Ira Ktena, Christopher Knutsen, Cyrus Rashtchian, Anant Nawalgaria, Jordi Pont-Tuset, Aida Nematzadeh REvolve: Reward Evolution with Large Language Models Using Human Feedback
Rishi Hazra, Alkis Sygkounas, Andreas Persson, Amy Loutfi, Pedro Zuidberg Dos Martires Reward Learning from Multiple Feedback Types
Yannick Metz, Andras Geiszl, Raphaël Baur, Mennatallah El-Assady Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning
Amrith Setlur, Chirag Nagpal, Adam Fisch, Xinyang Geng, Jacob Eisenstein, Rishabh Agarwal, Alekh Agarwal, Jonathan Berant, Aviral Kumar RFMamba: Frequency-Aware State Space Model for RF-Based Human-Centric Perception
Rui Zhang, Ruixu Geng, Yadong Li, Ruiyuan Song, Hanqin Gong, Dongheng Zhang, Yang Hu, Yan Chen RGB-Event ISP: The Dataset and Benchmark
Yunfan Lu, Yanlin Qian, Ziyang Rao, Junren Xiao, Liming Chen, Hui Xiong RMB: Comprehensively Benchmarking Reward Models in LLM Alignment
Enyu Zhou, Guodong Zheng, Binghai Wang, Zhiheng Xi, Shihan Dou, Rong Bao, Wei Shen, Limao Xiong, Jessica Fan, Yurong Mou, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang RMP-SAM: Towards Real-Time Multi-Purpose Segment Anything
Shilin Xu, Haobo Yuan, Qingyu Shi, Lu Qi, Jingbo Wang, Yibo Yang, Yining Li, Kai Chen, Yunhai Tong, Bernard Ghanem, Xiangtai Li, Ming-Hsuan Yang Robotouille: An Asynchronous Planning Benchmark for LLM Agents
Gonzalo Gonzalez-Pumariega, Leong Su Yean, Neha Sunkara, Sanjiban Choudhury RobuRCDet: Enhancing Robustness of Radar-Camera Fusion in Bird's Eye View for 3D Object Detection
Jingtong Yue, Zhiwei Lin, Xin Lin, Xiaoyu Zhou, Xiangtai Li, Lu Qi, Yongtao Wang, Ming-Hsuan Yang Robust Barycenter Estimation Using Semi-Unbalanced Neural Optimal Transport
Milena Gazdieva, Jaemoo Choi, Alexander Kolesov, Jaewoong Choi, Petr Mokrov, Alexander Korotin Robust Function-Calling for On-Device Language Model via Function Masking
Qiqiang Lin, Muning Wen, Qiuying Peng, Guanyu Nie, Junwei Liao, Jun Wang, Xiaoyun Mo, Jiamu Zhou, Cheng Cheng, Yin Zhao, Jun Wang, Weinan Zhang Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning
Shangding Gu, Laixi Shi, Muning Wen, Ming Jin, Eric Mazumdar, Yuejie Chi, Adam Wierman, Costas Spanos Robust Representation Consistency Model via Contrastive Denoising
Jiachen Lei, Julius Berner, Jiongxiao Wang, Zhongzhu Chen, Chaowei Xiao, Zhongjie Ba, Kui Ren, Jun Zhu, Anima Anandkumar Robust Root Cause Diagnosis Using In-Distribution Interventions
Lokesh Nagalapatti, Ashutosh Srivastava, Sunita Sarawagi, Amit Sharma Robustness Inspired Graph Backdoor Defense
Zhiwei Zhang, Minhua Lin, Junjie Xu, Zongyu Wu, Enyan Dai, Suhang Wang Robustness Reprogramming for Representation Learning
Zhichao Hou, MohamadAli Torkamani, Hamid Krim, Xiaorui Liu Rotated Runtime Smooth: Training-Free Activation Smoother for Accurate INT4 Inference
Ke Yi, Zengke Liu, Jianwei Zhang, Chengyuan Li, Tong Zhang, Junyang Lin, Jingren Zhou Round and Round We Go! What Makes Rotary Positional Encodings Useful?
Federico Barbero, Alex Vitvitskyi, Christos Perivolaropoulos, Razvan Pascanu, Petar Veličković ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQL
Yang Qin, Chao Chen, Zhihang Fu, Ze Chen, Dezhong Peng, Peng Hu, Jieping Ye RouteLLM: Learning to Route LLMs from Preference Data
Isaac Ong, Amjad Almahairi, Vincent Wu, Wei-Lin Chiang, Tianhao Wu, Joseph E. Gonzalez, M Waleed Kadous, Ion Stoica RRM: Robust Reward Model Training Mitigates Reward Hacking
Tianqi Liu, Wei Xiong, Jie Ren, Lichang Chen, Junru Wu, Rishabh Joshi, Yang Gao, Jiaming Shen, Zhen Qin, Tianhe Yu, Daniel Sohn, Anastasia Makarova, Jeremiah Zhe Liu, Yuan Liu, Bilal Piot, Abe Ittycheriah, Aviral Kumar, Mohammad Saleh RuAG: Learned-Rule-Augmented Generation for Large Language Models
Yudi Zhang, Pei Xiao, Lu Wang, Chaoyun Zhang, Meng Fang, Yali Du, Yevgeniy Puzyrev, Randolph Yao, Si Qin, Qingwei Lin, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang SafeDiffuser: Safe Planning with Diffusion Probabilistic Models
Wei Xiao, Tsun-Hsuan Wang, Chuang Gan, Ramin Hasani, Mathias Lechner, Daniela Rus Safety Alignment Should Be Made More than Just a Few Tokens Deep
Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, Xiao Ma, Subhrajit Roy, Ahmad Beirami, Prateek Mittal, Peter Henderson Safety Representations for Safer Policy Learning
Kaustubh Mani, Vincent Mai, Charlie Gauthier, Annie S Chen, Samer B. Nashed, Liam Paull SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation
Mingjie Li, Wai Man Si, Michael Backes, Yang Zhang, Yisen Wang SAM 2: Segment Anything in Images and Videos
Nikhila Ravi, Valentin Gabeur, Yuan-Ting Hu, Ronghang Hu, Chaitanya Ryali, Tengyu Ma, Haitham Khedr, Roman Rädle, Chloe Rolland, Laura Gustafson, Eric Mintun, Junting Pan, Kalyan Vasudev Alwala, Nicolas Carion, Chao-Yuan Wu, Ross Girshick, Piotr Dollar, Christoph Feichtenhofer SAM-CP: Marrying SAM with Composable Prompts for Versatile Segmentation
Pengfei Chen, Lingxi Xie, Xinyue Huo, Xuehui Yu, Xiaopeng Zhang, Yingfei Sun, Zhenjun Han, Qi Tian Samba: Synchronized Set-of-Sequences Modeling for Multiple Object Tracking
Mattia Segu, Luigi Piccinelli, Siyuan Li, Yung-Hsu Yang, Luc Van Gool, Bernt Schiele SaMer: A Scenario-Aware Multi-Dimensional Evaluator for Large Language Models
Kehua Feng, Keyan Ding, Jing Yu, Yiwen Qu, Zhiwen Chen, Chengfei Lv, Gang Yu, Qiang Zhang, Huajun Chen SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement
Yuqi Lin, Hengjia Li, Wenqi Shao, Zheng Yang, Jun Zhao, Xiaofei He, Ping Luo, Kaipeng Zhang SANA: Efficient High-Resolution Text-to-Image Synthesis with Linear Diffusion Transformers
Enze Xie, Junsong Chen, Junyu Chen, Han Cai, Haotian Tang, Yujun Lin, Zhekai Zhang, Muyang Li, Ligeng Zhu, Yao Lu, Song Han SANER: Annotation-Free Societal Attribute Neutralizer for Debiasing CLIP
Yusuke Hirota, Min-Hung Chen, Chien-Yi Wang, Yuta Nakashima, Yu-Chiang Frank Wang, Ryo Hachiuma SBSC: Step-by-Step Coding for Improving Mathematical Olympiad Performance
Kunal Singh, Ankan Biswas, Sayandeep Bhowmick, Pradeep Moturi, Siva Kishore Gollapalli SC-OmniGS: Self-Calibrating Omnidirectional Gaussian Splatting
Huajian Huang, Yingshu Chen, Longwei Li, Hui Cheng, Tristan Braud, Yajie Zhao, Sai-Kit Yeung Scalable Bayesian Learning with Posteriors
Samuel Duffield, Kaelan Donatella, Johnathan Chiu, Phoebe Klett, Daniel Simpson Scalable Benchmarking and Robust Learning for Noise-Free Ego-Motion and 3D Reconstruction from Noisy Video
Xiaohao Xu, Tianyi Zhang, Shibo Zhao, Xiang Li, Sibo Wang, Yongqi Chen, Ye Li, Bhiksha Raj, Matthew Johnson-Roberson, Sebastian Scherer, Xiaonan Huang Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics
Sebastian Sanokowski, Wilhelm Franz Berghammer, Haoyu Peter Wang, Martin Ennemoser, Sepp Hochreiter, Sebastian Lehner Scalable Extraction of Training Data from Aligned, Production Language Models
Milad Nasr, Javier Rando, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Florian Tramèr, Katherine Lee Scalable Influence and Fact Tracing for Large Language Model Pretraining
Tyler A. Chang, Dheeraj Rajagopal, Tolga Bolukbasi, Lucas Dixon, Ian Tenney Scalable Mechanistic Neural Networks
Jiale Chen, Dingling Yao, Adeel Pervez, Dan Alistarh, Francesco Locatello Scalable Universal T-Cell Receptor Embeddings from Adaptive Immune Repertoires
Paidamoyo Chapfuwa, Ilker Demirel, Lorenzo Pisani, Javier Zazo, Elon Portugaly, H. Jabran Zahid, Julia Greissl Scale-Aware Recognition in Satellite Images Under Resource Constraints
Shreelekha Revankar, Cheng Perng Phoo, Utkarsh Mall, Bharath Hariharan, Kavita Bala Scale-Free Graph-Language Models
Jianglin Lu, Yixuan Liu, Yitian Zhang, Yun Fu Scaling and Evaluating Sparse Autoencoders
Leo Gao, Tom Dupre la Tour, Henk Tillman, Gabriel Goh, Rajan Troll, Alec Radford, Ilya Sutskever, Jan Leike, Jeffrey Wu Scaling Diffusion Language Models via Adaptation from Autoregressive Models
Shansan Gong, Shivam Agarwal, Yizhe Zhang, Jiacheng Ye, Lin Zheng, Mukai Li, Chenxin An, Peilin Zhao, Wei Bi, Jiawei Han, Hao Peng, Lingpeng Kong Scaling FP8 Training to Trillion-Token LLMs
Maxim Fishman, Brian Chmiel, Ron Banner, Daniel Soudry Scaling Large Language Model-Based Multi-Agent Collaboration
Chen Qian, Zihao Xie, YiFei Wang, Wei Liu, Kunlun Zhu, Hanchen Xia, Yufan Dang, Zhuoyun Du, Weize Chen, Cheng Yang, Zhiyuan Liu, Maosong Sun Scaling Laws for Downstream Task Performance in Machine Translation
Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo Scaling Laws for Precision
Tanishq Kumar, Zachary Ankner, Benjamin Frederick Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Re, Aditi Raghunathan Scaling Long Context Training Data by Long-Distance Referrals
Yonghao Zhuang, Lanxiang Hu, Longfei Yun, Souvik Kundu, Zhengzhong Liu, Eric P. Xing, Hao Zhang Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining
Jie Cheng, Ruixi Qiao, Yingwei Ma, Binhua Li, Gang Xiong, Qinghai Miao, Yongbin Li, Yisheng Lv Scaling Optimal LR Across Token Horizons
Johan Bjorck, Alon Benhaim, Vishrav Chaudhary, Furu Wei, Xia Song Scaling Speech-Text Pre-Training with Synthetic Interleaved Data
Aohan Zeng, Zhengxiao Du, Mingdao Liu, Lei Zhang, Shengmin Jiang, Yuxiao Dong, Jie Tang Scaling Transformers for Low-Bitrate High-Quality Speech Coding
Julian D Parker, Anton Smirnov, Jordi Pons, Cj Carr, Zack Zukowski, Zach Evans, Xubo Liu Scaling up Masked Diffusion Models on Text
Shen Nie, Fengqi Zhu, Chao Du, Tianyu Pang, Qian Liu, Guangtao Zeng, Min Lin, Chongxuan Li Scaling Wearable Foundation Models
Girish Narayanswamy, Xin Liu, Kumar Ayush, Yuzhe Yang, Xuhai Xu, Shun Liao, Jake Garrison, Shyam A. Tailor, Jacob Sunshine, Yun Liu, Tim Althoff, Shrikanth Narayanan, Pushmeet Kohli, Jiening Zhan, Mark Malhotra, Shwetak Patel, Samy Abdel-Ghaffar, Daniel McDuff SCBench: A KV Cache-Centric Analysis of Long-Context Methods
Yucheng Li, Huiqiang Jiang, Qianhui Wu, Xufang Luo, Surin Ahn, Chengruidong Zhang, Amir H. Abdi, Dongsheng Li, Jianfeng Gao, Yuqing Yang, Lili Qiu ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery
Ziru Chen, Shijie Chen, Yuting Ning, Qianheng Zhang, Boshi Wang, Botao Yu, Yifei Li, Zeyi Liao, Chen Wei, Zitong Lu, Vishal Dey, Mingyi Xue, Frazier N. Baker, Benjamin Burns, Daniel Adu-Ampratwum, Xuhui Huang, Xia Ning, Song Gao, Yu Su, Huan Sun SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding
Sihang Li, Jin Huang, Jiaxi Zhuang, Yaorui Shi, Xiaochen Cai, Mingjun Xu, Xiang Wang, Linfeng Zhang, Guolin Ke, Hengxing Cai ScImage: How Good Are Multimodal Large Language Models at Scientific Text-to-Image Generation?
Leixin Zhang, Steffen Eger, Yinjie Cheng, Weihe Zhai, Jonas Belouadi, Fahimeh Moafian, Zhixue Zhao SCOPE: A Self-Supervised Framework for Improving Faithfulness in Conditional Text Generation
Song Duong, Florian Le Bronnec, Alexandre Allauzen, Vincent Guigue, Alberto Lumbreras, Laure Soulier, Patrick Gallinari SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning
Yichen Wu, Hongming Piao, Long-Kai Huang, Renzhen Wang, Wanhua Li, Hanspeter Pfister, Deyu Meng, Kede Ma, Ying Wei Searching for Optimal Solutions with LLMs via Bayesian Optimization
Dhruv Agarwal, Manoj Ghuhan Arivazhagan, Rajarshi Das, Sandesh Swamy, Sopan Khosla, Rashmi Gangadharaiah SEBRA : Debiasing Through Self-Guided Bias Ranking
Adarsh Kappiyath, Abhra Chaudhuri, Ajay Kumar Jaiswal, Ziquan Liu, Yunpeng Li, Xiatian Zhu, Lu Yin SeCom: On Memory Construction and Retrieval for Personalized Conversational Agents
Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Xufang Luo, Hao Cheng, Dongsheng Li, Yuqing Yang, Chin-Yew Lin, H. Vicky Zhao, Lili Qiu, Jianfeng Gao SecureGS: Boosting the Security and Fidelity of 3D Gaussian Splatting Steganography
Xuanyu Zhang, Jiarui Meng, Zhipei Xu, Shuzhou Yang, Yanmin Wu, Ronggang Wang, Jian Zhang SeedLM: Compressing LLM Weights into Seeds of Pseudo-Random Generators
Rasoul Shafipour, David Harrison, Maxwell Horton, Jeffrey Marker, Houman Bedayat, Sachin Mehta, Mohammad Rastegari, Mahyar Najibi, Saman Naderiparizi Seeing Eye to AI: Human Alignment via Gaze-Based Response Rewards for Large Language Models
Angela Lopez-Cardona, Carlos Segura, Alexandros Karatzoglou, Sergi Abadal, Ioannis Arapakis SegLLM: Multi-Round Reasoning Segmentation with Large Language Models
XuDong Wang, Shaolun Zhang, Shufan Li, Kehan Li, Konstantinos Kallidromitis, Yusuke Kato, Kazuki Kozuka, Trevor Darrell Segment Any 3D Object with Language
Seungjun Lee, Yuyang Zhao, Gim Hee Lee Selective Aggregation for Low-Rank Adaptation in Federated Learning
Pengxin Guo, Shuang Zeng, Yanran Wang, Huijie Fan, Feifei Wang, Liangqiong Qu Selective Attention Improves Transformer
Yaniv Leviathan, Matan Kalman, Yossi Matias Selective Unlearning via Representation Erasure Using Domain Adversarial Training
Nazanin Mohammadi Sepahvand, Eleni Triantafillou, Hugo Larochelle, Doina Precup, James J. Clark, Daniel M. Roy, Gintare Karolina Dziugaite Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
Ce Zhang, Zifu Wan, Zhehan Kan, Martin Q. Ma, Simon Stepputtis, Deva Ramanan, Russ Salakhutdinov, Louis-Philippe Morency, Katia P. Sycara, Yaqi Xie Self-Evolved Reward Learning for LLMs
Chenghua Huang, Zhizhen Fan, Lu Wang, Fangkai Yang, Pu Zhao, Zeqi Lin, Qingwei Lin, Dongmei Zhang, Saravan Rajmohan, Qi Zhang Self-Evolving Multi-Agent Collaboration Networks for Software Development
Yue Hu, Yuzhu Cai, Yaxin Du, Xinyu Zhu, Xiangrui Liu, Zijie Yu, Yuchen Hou, Shuo Tang, Siheng Chen Self-Improvement in Language Models: The Sharpening Mechanism
Audrey Huang, Adam Block, Dylan J Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy Self-Improving Robust Preference Optimization
Eugene Choi, Arash Ahmadian, Matthieu Geist, Olivier Pietquin, Mohammad Gheshlaghi Azar Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts
Junmo Kang, Leonid Karlinsky, Hongyin Luo, Zhen Wang, Jacob A Hansen, James R. Glass, David Daniel Cox, Rameswar Panda, Rogerio Feris, Alan Ritter Self-Play Preference Optimization for Language Model Alignment
Yue Wu, Zhiqing Sun, Huizhuo Yuan, Kaixuan Ji, Yiming Yang, Quanquan Gu Semantic Image Inversion and Editing Using Rectified Stochastic Differential Equations
Litu Rout, Yujia Chen, Nataniel Ruiz, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu Semantix: An Energy-Guided Sampler for Semantic Style Transfer
Huiang He, Minghui Hu, Chuanxia Zheng, Chaoyue Wang, Tat-Jen Cham Sensor-Invariant Tactile Representation
Harsh Gupta, Yuchen Mo, Shengmiao Jin, Wenzhen Yuan Separation Power of Equivariant Neural Networks
Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning
Md Rifat Arefin, Gopeshh Subbaraj, Nicolas Gontier, Yann LeCun, Irina Rish, Ravid Shwartz-Ziv, Christopher Pal Sequential Controlled Langevin Diffusions
Junhua Chen, Lorenz Richter, Julius Berner, Denis Blessing, Gerhard Neumann, Anima Anandkumar SeRA: Self-Reviewing and Alignment of LLMs Using Implicit Reward Margins
Jongwoo Ko, Saket Dingliwal, Bhavana Ganesh, Sailik Sengupta, Sravan Babu Bodapati, Aram Galstyan SFS: Smarter Code Space Search Improves LLM Inference Scaling
Jonathan Light, Yue Wu, Yiyou Sun, Wenchao Yu, Yanchi Liu, Xujiang Zhao, Ziniu Hu, Haifeng Chen, Wei Cheng SG-I2V: Self-Guided Trajectory Control in Image-to-Video Generation
Koichi Namekata, Sherwin Bahmani, Ziyi Wu, Yash Kant, Igor Gilitschenski, David B. Lindell Sharpness-Aware Black-Box Optimization
Feiyang Ye, Yueming Lyu, Xuehao Wang, Masashi Sugiyama, Yu Zhang, Ivor Tsang Shedding Light on Time Series Classification Using Interpretability Gated Networks
Yunshi Wen, Tengfei Ma, Ronny Luss, Debarun Bhattacharjya, Achille Fokoue, Anak Agung Julius Shh, Don't Say That! Domain Certification in LLMs
Cornelius Emde, Alasdair Paren, Preetham Arvind, Maxime Guillaume Kayser, Tom Rainforth, Thomas Lukasiewicz, Philip Torr, Adel Bibi ShortcutsBench: A Large-Scale Real-World Benchmark for API-Based Agents
Haiyang Shen, Yue Li, Desong Meng, Dongqi Cai, Sheng Qi, Li Zhang, Mengwei Xu, Yun Ma Should VLMs Be Pre-Trained with Image Data?
Sedrick Keh, Jean Mercat, Samir Yitzhak Gadre, Kushal Arora, Igor Vasiljevic, Benjamin Burchfiel, Shuran Song, Russ Tedrake, Thomas Kollar, Ludwig Schmidt, Achal Dave Show-O: One Single Transformer to Unify Multimodal Understanding and Generation
Jinheng Xie, Weijia Mao, Zechen Bai, David Junhao Zhang, Weihao Wang, Kevin Qinghong Lin, Yuchao Gu, Zhijie Chen, Zhenheng Yang, Mike Zheng Shou Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes
Georg Manten, Cecilia Casolo, Emilio Ferrucci, Søren Wengel Mogensen, Cristopher Salvi, Niki Kilbertus SIM: Surface-Based fMRI Analysis for Inter-Subject Multimodal Decoding from Movie-Watching Experiments
Simon Dahan, Gabriel Bénédict, Logan Zane John Williams, Yourong Guo, Daniel Rueckert, Robert Leech, Emma Claire Robinson SimBa: Simplicity Bias for Scaling up Parameters in Deep Reinforcement Learning
Hojoon Lee, Dongyoon Hwang, Donghu Kim, Hyunseung Kim, Jun Jet Tai, Kaushik Subramanian, Peter R. Wurman, Jaegul Choo, Peter Stone, Takuma Seno SiMHand: Mining Similar Hands for Large-Scale 3D Hand Pose Pre-Training
Nie Lin, Takehiko Ohkawa, Yifei Huang, Mingfang Zhang, Minjie Cai, Ming Li, Ryosuke Furuta, Yoichi Sato SimPER: A Minimalist Approach to Preference Alignment Without Hyperparameters
Teng Xiao, Yige Yuan, Zhengyu Chen, Mingxiao Li, Shangsong Liang, Zhaochun Ren, Vasant G Honavar Simple Guidance Mechanisms for Discrete Diffusion Models
Yair Schiff, Subham Sekhar Sahoo, Hao Phung, Guanghan Wang, Sam Boshar, Hugo Dalla-torre, Bernardo P de Almeida, Alexander M Rush, Thomas Pierrot, Volodymyr Kuleshov Simple ReFlow: Improved Techniques for Fast Flow Models
Beomsu Kim, Yu-Guan Hsieh, Michal Klein, Marco Cuturi, Jong Chul Ye, Bahjat Kawar, James Thornton Simplifying Deep Temporal Difference Learning
Matteo Gallici, Mattie Fellows, Benjamin Ellis, Bartomeu Pou, Ivan Masmitja, Jakob Nicolaus Foerster, Mario Martin Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks
Hanling Tian, Yuhang Liu, Mingzhen He, Zhengbao He, Zhehao Huang, Ruikai Yang, Xiaolin Huang SINGER: Stochastic Network Graph Evolving Operator for High Dimensional PDEs
Mingquan Feng, Yixin Huang, Weixin Liao, Yuhong Liu, Yizhou Liu, Junchi Yan SiReRAG: Indexing Similar and Related Information for Multihop Reasoning
Nan Zhang, Prafulla Kumar Choubey, Alexander Fabbri, Gabriel Bernadett-Shapiro, Rui Zhang, Prasenjit Mitra, Caiming Xiong, Chien-Sheng Wu Sitcom-Crafter: A Plot-Driven Human Motion Generation System in 3D Scenes
Jianqi Chen, Panwen Hu, Xiaojun Chang, Zhenwei Shi, Michael Kampffmeyer, Xiaodan Liang Skill Expansion and Composition in Parameter Space
Tenglong Liu, Jianxiong Li, Yinan Zheng, Haoyi Niu, Yixing Lan, Xin Xu, Xianyuan Zhan SleepSMC: Ubiquitous Sleep Staging via Supervised Multimodal Coordination
Shuo Ma, Yingwei Zhang, Yiqiang Chen, Hualei Wang, Yuan Jin, Wei Zhang, Ziyu Jia SLMRec: Distilling Large Language Models into Small for Sequential Recommendation
Wujiang Xu, Qitian Wu, Zujie Liang, Jiaojiao Han, Xuying Ning, Yunxiao Shi, Wenfang Lin, Yongfeng Zhang SlowFast-VGen: Slow-Fast Learning for Action-Driven Long Video Generation
Yining Hong, Beide Liu, Maxine Wu, Yuanhao Zhai, Kai-Wei Chang, Linjie Li, Kevin Lin, Chung-Ching Lin, Jianfeng Wang, Zhengyuan Yang, Ying Nian Wu, Lijuan Wang Small Models Are LLM Knowledge Triggers for Medical Tabular Prediction
Jiahuan Yan, Jintai Chen, Chaowen Hu, Bo Zheng, Yaojun Hu, Jimeng Sun, Jian Wu SmartRAG: Jointly Learn RAG-Related Tasks from the Environment Feedback
Jingsheng Gao, Linxu Li, Ke Ji, Weiyuan Li, Yixin Lian, Yuzhuo Fu, Bin Dai SMI-Editor: Edit-Based SMILES Language Model with Fragment-Level Supervision
Kangjie Zheng, Siyue Liang, Junwei Yang, Bin Feng, Zequn Liu, Wei Ju, Zhiping Xiao, Ming Zhang SMITE: Segment Me in TimE
Amirhossein Alimohammadi, Sauradip Nag, Saeid Asgari, Andrea Tagliasacchi, Ghassan Hamarneh, Ali Mahdavi Amiri SOAP: Improving and Stabilizing Shampoo Using Adam for Language Modeling
Nikhil Vyas, Depen Morwani, Rosie Zhao, Itai Shapira, David Brandfonbrener, Lucas Janson, Sham M. Kakade SoftMatcha: A Soft and Fast Pattern Matcher for Billion-Scale Corpus Searches
Hiroyuki Deguchi, Go Kamoda, Yusuke Matsushita, Chihiro Taguchi, Kohei Suenaga, Masaki Waga, Sho Yokoi Solving Hidden Monotone Variational Inequalities with Surrogate Losses
Ryan D'Orazio, Danilo Vucetic, Zichu Liu, Junhyung Lyle Kim, Ioannis Mitliagkas, Gauthier Gidel SONICS: Synthetic or Not - Identifying Counterfeit Songs
Md Awsafur Rahman, Zaber Ibn Abdul Hakim, Najibul Haque Sarker, Bishmoy Paul, Shaikh Anowarul Fattah SOO-Bench: Benchmarks for Evaluating the Stability of Offline Black-Box Optimization
Hong Qian, Yiyi Zhu, Xiang Shu, Shuo Liu, Yaolin Wen, Xin An, Huakang Lu, Aimin Zhou, Ke Tang, Yang Yu SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal
Tinghao Xie, Xiangyu Qi, Yi Zeng, Yangsibo Huang, Udari Madhushani Sehwag, Kaixuan Huang, Luxi He, Boyi Wei, Dacheng Li, Ying Sheng, Ruoxi Jia, Bo Li, Kai Li, Danqi Chen, Peter Henderson, Prateek Mittal Sort-Free Gaussian Splatting via Weighted Sum Rendering
Qiqi Hou, Randall Rauwendaal, Zifeng Li, Hoang Le, Farzad Farhadzadeh, Fatih Porikli, Alexei Bourd, Amir Said SoundCTM: Unifying Score-Based and Consistency Models for Full-Band Text-to-Sound Generation
Koichi Saito, Dongjun Kim, Takashi Shibuya, Chieh-Hsin Lai, Zhi Zhong, Yuhta Takida, Yuki Mitsufuji Spa-Bench: A Comprehensive Benchmark for Smartphone Agent Evaluation
Jingxuan Chen, Derek Yuen, Bin Xie, Yuhao Yang, Gongwei Chen, Zhihao Wu, Li Yixing, Xurui Zhou, Weiwen Liu, Shuai Wang, Kaiwen Zhou, Rui Shao, Liqiang Nie, Yasheng Wang, Jianye Hao, Jun Wang, Kun Shao SPA: 3D Spatial-Awareness Enables Effective Embodied Representation
Haoyi Zhu, Honghui Yang, Yating Wang, Jiange Yang, Limin Wang, Tong He SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training
Tianjin Huang, Ziquan Zhu, Gaojie Jin, Lu Liu, Zhangyang Wang, Shiwei Liu SPaR: Self-Play with Tree-Search Refinement to Improve Instruction-Following in Large Language Models
Jiale Cheng, Xiao Liu, Cunxiang Wang, Xiaotao Gu, Yida Lu, Dan Zhang, Yuxiao Dong, Jie Tang, Hongning Wang, Minlie Huang Sparse Autoencoders Do Not Find Canonical Units of Analysis
Patrick Leask, Bart Bussmann, Michael T Pearce, Joseph Isaac Bloom, Curt Tigges, Noura Al Moubayed, Lee Sharkey, Neel Nanda Sparse Learning for State Space Models on Mobile
Xuan Shen, Hangyu Zheng, Yifan Gong, Zhenglun Kong, Changdi Yang, Zheng Zhan, Yushu Wu, Xue Lin, Yanzhi Wang, Pu Zhao, Wei Niu SparsyFed: Sparse Adaptive Federated Learning
Adriano Guastella, Lorenzo Sani, Alex Iacob, Alessio Mora, Paolo Bellavista, Nicholas Donald Lane Specialized Foundation Models Struggle to Beat Supervised Baselines
Zongzhe Xu, Ritvik Gupta, Wenduo Cheng, Alexander Shen, Junhong Shen, Ameet Talwalkar, Mikhail Khodak Spectro-Riemannian Graph Neural Networks
Karish Grover, Haiyang Yu, Xiang Song, Qi Zhu, Han Xie, Vassilis N. Ioannidis, Christos Faloutsos Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling
Wenda Xu, Rujun Han, Zifeng Wang, Long Le, Dhruv Madeka, Lei Li, William Yang Wang, Rishabh Agarwal, Chen-Yu Lee, Tomas Pfister Speculative RAG: Enhancing Retrieval Augmented Generation Through Drafting
Zilong Wang, Zifeng Wang, Long Le, Steven Zheng, Swaroop Mishra, Vincent Perot, Yuwei Zhang, Anush Mattapalli, Ankur Taly, Jingbo Shang, Chen-Yu Lee, Tomas Pfister Speech Robust Bench: A Robustness Benchmark for Speech Recognition
Muhammad A Shah, David Solans Noguero, Mikko A. Heikkilä, Bhiksha Raj, Nicolas Kourtellis Spherical Tree-Sliced Wasserstein Distance
Hoang V. Tran, Thanh Chu, Minh-Khoi Nguyen-Nhat, Huyen Trang Pham, Tam Le, Tan Minh Nguyen Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows
Fangyu Lei, Jixuan Chen, Yuxiao Ye, Ruisheng Cao, Dongchan Shin, Hongjin Su, Zhaoqing Suo, Hongcheng Gao, Wenjing Hu, Pengcheng Yin, Victor Zhong, Caiming Xiong, Ruoxi Sun, Qian Liu, Sida Wang, Tao Yu SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-Based Spiking
Xingrun Xing, Boyan Gao, Zheng Liu, David A. Clifton, Shitao Xiao, Wanpeng Zhang, Li Du, Zheng Zhang, Guoqi Li, Jiajun Zhang Spiking Vision Transformer with Saccadic Attention
Shuai Wang, Malu Zhang, Dehao Zhang, Ammar Belatreche, Yichen Xiao, Yu Liang, Yimeng Shan, Qian Sun, Enqi Zhang, Yang Yang SpinQuant: LLM Quantization with Learned Rotations
Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort SplatFormer: Point Transformer for Robust 3D Gaussian Splatting
Yutong Chen, Marko Mihajlovic, Xiyi Chen, Yiming Wang, Sergey Prokudin, Siyu Tang SPORTU: A Comprehensive Sports Understanding Benchmark for Multimodal Large Language Models
Haotian Xia, Zhengbang Yang, Junbo Zou, Rhys Tracy, Yuqing Wang, Chi Lu, Christopher Lai, Yanjun He, Xun Shao, Zhuoqing Xie, Yuan-fang Wang, Weining Shen, Hanjie Chen Spreading Out-of-Distribution Detection on Graphs
Daeho Um, Jongin Lim, Sunoh Kim, Yuneil Yeo, Yoonho Jung SRSA: Skill Retrieval and Adaptation for Robotic Assembly Tasks
Yijie Guo, Bingjie Tang, Iretiayo Akinola, Dieter Fox, Abhishek Gupta, Yashraj Narang Stable Segment Anything Model
Qi Fan, Xin Tao, Lei Ke, Mingqiao Ye, Di Zhang, Pengfei Wan, Yu-Wing Tai, Chi-Keung Tang STAFF: Speculative Coreset Selection for Task-Specific Fine-Tuning
Xiaoyu Zhang, Juan Zhai, Shiqing Ma, Chao Shen, Tianlin Li, Weipeng Jiang, Yang Liu STAMP: Scalable Task- and Model-Agnostic Collaborative Perception
Xiangbo Gao, Runsheng Xu, Jiachen Li, Ziran Wang, Zhiwen Fan, Zhengzhong Tu Standardizing Structural Causal Models
Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schölkopf, Andreas Krause STAR: Stability-Inducing Weight Perturbation for Continual Learning
Masih Eskandar, Tooba Imtiaz, Davin Hill, Zifeng Wang, Jennifer Dy STAR: Synthesis of Tailored Architectures
Armin W Thomas, Rom Parnichkun, Alexander Amini, Stefano Massaroli, Michael Poli Statistical Advantages of Perturbing Cosine Router in Mixture of Experts
Huy Nguyen, Pedram Akbarian, Huyen Trang Pham, Thien Trang Nguyen Vu, Shujian Zhang, Nhat Ho STBLLM: Breaking the 1-Bit Barrier with Structured Binary LLMs
Peijie Dong, Lujun Li, Yuedong Zhong, DaYou Du, Ruibo Fan, Yuhan Chen, Zhenheng Tang, Qiang Wang, Wei Xue, Yike Guo, Xiaowen Chu Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction
Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Pranam Chatterjee, Alexander Tong, Joey Bose Steering Protein Family Design Through Profile Bayesian Flow
Jingjing Gong, Yu Pei, Siyu Long, Yuxuan Song, Zhe Zhang, Wenhao Huang, Ziyao Cao, Shuyi Zhang, Hao Zhou, Wei-Ying Ma Step-by-Step Reasoning for Math Problems via Twisted Sequential Monte Carlo
Shengyu Feng, Xiang Kong, Shuang Ma, Aonan Zhang, Dong Yin, Chong Wang, Ruoming Pang, Yiming Yang Stiefel Flow Matching for Moment-Constrained Structure Elucidation
Austin Henry Cheng, Alston Lo, Kin Long Kelvin Lee, Santiago Miret, Alan Aspuru-Guzik Stochastic Bandits Robust to Adversarial Attacks
Xuchuang Wang, Maoli Liu, Jinhang Zuo, Xutong Liu, John C.S. Lui, Mohammad Hajiesmaili STORM: Spatio-TempOral Reconstruction Model for Large-Scale Outdoor Scenes
Jiawei Yang, Jiahui Huang, Boris Ivanovic, Yuxiao Chen, Yan Wang, Boyi Li, Yurong You, Apoorva Sharma, Maximilian Igl, Peter Karkus, Danfei Xu, Yue Wang, Marco Pavone Straight to Zero: Why Linearly Decaying the Learning Rate to Zero Works Best for LLMs
Shane Bergsma, Nolan Simran Dey, Gurpreet Gosal, Gavia Gray, Daria Soboleva, Joel Hestness STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning
Marius Memmel, Jacob Berg, Bingqing Chen, Abhishek Gupta, Jonathan Francis Strategic Classification with Externalities
Safwan Hossain, Evi Micha, Yiling Chen, Ariel D. Procaccia Strategist: Self-Improvement of LLM Decision Making via Bi-Level Tree Search
Jonathan Light, Min Cai, Weiqin Chen, Guanzhi Wang, Xiusi Chen, Wei Cheng, Yisong Yue, Ziniu Hu Streaming Algorithms for $\ell_p$ Flows and $\ell_p$ Regression
Amit Chakrabarti, Jeffrey Jiang, David Woodruff, Taisuke Yasuda Streaming Video Question-Answering with In-Context Video KV-Cache Retrieval
Shangzhe Di, Zhelun Yu, Guanghao Zhang, Haoyuan Li, TaoZhong, Hao Cheng, Bolin Li, Wanggui He, Fangxun Shu, Hao Jiang Streamlining Prediction in Bayesian Deep Learning
Rui Li, Marcus Klasson, Arno Solin, Martin Trapp Streamlining Redundant Layers to Compress Large Language Models
Xiaodong Chen, Yuxuan Hu, Jing Zhang, Yanling Wang, Cuiping Li, Hong Chen Strong Model Collapse
Elvis Dohmatob, Yunzhen Feng, Arjun Subramonian, Julia Kempe StructRAG: Boosting Knowledge Intensive Reasoning of LLMs via Inference-Time Hybrid Information Structurization
Zhuoqun Li, Xuanang Chen, Haiyang Yu, Hongyu Lin, Yaojie Lu, Qiaoyu Tang, Fei Huang, Xianpei Han, Le Sun, Yongbin Li Structural-Entropy-Based Sample Selection for Efficient and Effective Learning
Tianchi Xie, Jiangning Zhu, Guozu Ma, Minzhi Lin, Wei Chen, Weikai Yang, Shixia Liu Structure Language Models for Protein Conformation Generation
Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Chence Shi, Hongyu Guo, Yoshua Bengio, Jian Tang Student-Informed Teacher Training
Nico Messikommer, Jiaxu Xing, Elie Aljalbout, Davide Scaramuzza Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning
Samuel Garcin, Trevor McInroe, Pablo Samuel Castro, Christopher G. Lucas, David Abel, Prakash Panangaden, Stefano V Albrecht Style Outweighs Substance: Failure Modes of LLM Judges in Alignment Benchmarking
Benjamin Feuer, Micah Goldblum, Teresa Datta, Sanjana Nambiar, Raz Besaleli, Samuel Dooley, Max Cembalest, John P Dickerson Subgraph Federated Learning for Local Generalization
Sungwon Kim, Yoonho Lee, Yunhak Oh, Namkyeong Lee, Sukwon Yun, Junseok Lee, Sein Kim, Carl Yang, Chanyoung Park Subtask-Aware Visual Reward Learning from Segmented Demonstrations
Changyeon Kim, Minho Heo, Doohyun Lee, Honglak Lee, Jinwoo Shin, Joseph J Lim, Kimin Lee Sufficient Context: A New Lens on Retrieval Augmented Generation Systems
Hailey Joren, Jianyi Zhang, Chun-Sung Ferng, Da-Cheng Juan, Ankur Taly, Cyrus Rashtchian Support Is All You Need for Certified VAE Training
Changming Xu, Debangshu Banerjee, Deepak Vasisht, Gagandeep Singh SurFhead: Affine Rig Blending for Geometrically Accurate 2D Gaussian Surfel Head Avatars
Jaeseong Lee, Taewoong Kang, Marcel Buehler, Min-Jung Kim, Sungwon Hwang, Junha Hyung, Hyojin Jang, Jaegul Choo Surprising Effectiveness of Pretraining Ternary Language Model at Scale
Ayush Kaushal, Tejas Vaidhya, Arnab Kumar Mondal, Tejas Pandey, Aaryan Bhagat, Irina Rish SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understanding
Jian Chen, Ruiyi Zhang, Yufan Zhou, Tong Yu, Franck Dernoncourt, Jiuxiang Gu, Ryan A. Rossi, Changyou Chen, Tong Sun SVBench: A Benchmark with Temporal Multi-Turn Dialogues for Streaming Video Understanding
Zhenyu Yang, Yuhang Hu, Zemin Du, Dizhan Xue, Shengsheng Qian, Jiahong Wu, Fan Yang, Weiming Dong, Changsheng Xu SVDQuant: Absorbing Outliers by Low-Rank Component for 4-Bit Diffusion Models
Muyang Li, Yujun Lin, Zhekai Zhang, Tianle Cai, Xiuyu Li, Junxian Guo, Enze Xie, Chenlin Meng, Jun-Yan Zhu, Song Han SVG: 3D Stereoscopic Video Generation via Denoising Frame Matrix
Peng Dai, Feitong Tan, Qiangeng Xu, David Futschik, Ruofei Du, Sean Fanello, Xiaojuan Qi, Yinda Zhang SWE-Bench Multimodal: Do AI Systems Generalize to Visual Software Domains?
John Yang, Carlos E Jimenez, Alex L Zhang, Kilian Lieret, Joyce Yang, Xindi Wu, Ori Press, Niklas Muennighoff, Gabriel Synnaeve, Karthik R Narasimhan, Diyi Yang, Sida Wang, Ofir Press SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement
Antonis Antoniades, Albert Örwall, Kexun Zhang, Yuxi Xie, Anirudh Goyal, William Yang Wang SWEb: A Large Web Dataset for the Scandinavian Languages
Tobias Norlund, Tim Isbister, Amaru Cuba Gyllensten, Paul Gabriel dos Santos, Danila Petrelli, Ariel Ekgren, Magnus Sahlgren Swing-by Dynamics in Concept Learning and Compositional Generalization
Yongyi Yang, Core Francisco Park, Ekdeep Singh Lubana, Maya Okawa, Wei Hu, Hidenori Tanaka Sylber: Syllabic Embedding Representation of Speech from Raw Audio
Cheol Jun Cho, Nicholas Lee, Akshat Gupta, Dhruv Agarwal, Ethan Chen, Alan Black, Gopala Anumanchipalli SymDiff: Equivariant Diffusion via Stochastic Symmetrisation
Leo Zhang, Kianoosh Ashouritaklimi, Yee Whye Teh, Rob Cornish SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models
Daniel Levy, Siba Smarak Panigrahi, Sékou-Oumar Kaba, Qiang Zhu, Kin Long Kelvin Lee, Mikhail Galkin, Santiago Miret, Siamak Ravanbakhsh SynCamMaster: Synchronizing Multi-Camera Video Generation from Diverse Viewpoints
Jianhong Bai, Menghan Xia, Xintao Wang, Ziyang Yuan, Zuozhu Liu, Haoji Hu, Pengfei Wan, Di Zhang Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling
Cristian Rodriguez-Opazo, Ehsan Abbasnejad, Damien Teney, Hamed Damirchi, Edison Marrese-Taylor, Anton van den Hengel Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning
Zijian Li, Shunxing Fan, Yujia Zheng, Ignavier Ng, Shaoan Xie, Guangyi Chen, Xinshuai Dong, Ruichu Cai, Kun Zhang SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints
Miruna Cretu, Charles Harris, Ilia Igashov, Arne Schneuing, Marwin Segler, Bruno Correia, Julien Roy, Emmanuel Bengio, Pietro Lio Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo
João Loula, Benjamin LeBrun, Li Du, Ben Lipkin, Clemente Pasti, Gabriel Grand, Tianyu Liu, Yahya Emara, Marjorie Freedman, Jason Eisner, Ryan Cotterell, Vikash Mansinghka, Alexander K. Lew, Tim Vieira, Timothy J. O'Donnell Synthetic Continued Pretraining
Zitong Yang, Neil Band, Shuangping Li, Emmanuel Candes, Tatsunori Hashimoto Synthio: Augmenting Small-Scale Audio Classification Datasets with Synthetic Data
Sreyan Ghosh, Sonal Kumar, Zhifeng Kong, Rafael Valle, Bryan Catanzaro, Dinesh Manocha SysBench: Can LLMs Follow System Message?
Yanzhao Qin, Tao Zhang, Tao Zhang, Yanjun Shen, Wenjing Luo, Sunhaoze, Yan Zhang, Yujing Qiao, Weipeng Chen, Zenan Zhou, Wentao Zhang, Bin Cui System 1.x: Learning to Balance Fast and Slow Planning with Language Models
Swarnadeep Saha, Archiki Prasad, Justin Chen, Peter Hase, Elias Stengel-Eskin, Mohit Bansal Systematic Outliers in Large Language Models
Yongqi An, Xu Zhao, Tao Yu, Ming Tang, Jinqiao Wang Systems with Switching Causal Relations: A Meta-Causal Perspective
Moritz Willig, Tim Tobiasch, Florian Peter Busch, Jonas Seng, Devendra Singh Dhami, Kristian Kersting T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data
Hugo Thimonier, José Lucas De Melo Costa, Fabrice Popineau, Arpad Rimmel, Bich-Liên Doan T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching
Zizheng Pan, Bohan Zhuang, De-An Huang, Weili Nie, Zhiding Yu, Chaowei Xiao, Jianfei Cai, Anima Anandkumar TabDiff: A Mixed-Type Diffusion Model for Tabular Data Generation
Juntong Shi, Minkai Xu, Harper Hua, Hengrui Zhang, Stefano Ermon, Jure Leskovec TabWak: A Watermark for Tabular Diffusion Models
Chaoyi Zhu, Jiayi Tang, Jeroen M. Galjaard, Pin-Yu Chen, Robert Birke, Cornelis Bos, Lydia Y. Chen Tailoring Mixup to Data for Calibration
Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc Talking Turns: Benchmarking Audio Foundation Models on Turn-Taking Dynamics
Siddhant Arora, Zhiyun Lu, Chung-Cheng Chiu, Ruoming Pang, Shinji Watanabe Taming Transformer Without Using Learning Rate Warmup
Xianbiao Qi, Yelin He, Jiaquan Ye, Chun-Guang Li, Bojia Zi, Xili Dai, Qin Zou, Rong Xiao Tamper-Resistant Safeguards for Open-Weight LLMs
Rishub Tamirisa, Bhrugu Bharathi, Long Phan, Andy Zhou, Alice Gatti, Tarun Suresh, Maxwell Lin, Justin Wang, Rowan Wang, Ron Arel, Andy Zou, Dawn Song, Bo Li, Dan Hendrycks, Mantas Mazeika TASAR: Transfer-Based Attack on Skeletal Action Recognition
Yunfeng Diao, Baiqi Wu, Ruixuan Zhang, Ajian Liu, Xiaoshuai Hao, Xingxing Wei, Meng Wang, He Wang TaskGalaxy: Scaling Multi-Modal Instruction Fine-Tuning with Tens of Thousands Vision Task Types
Jiankang Chen, Tianke Zhang, Changyi Liu, Haojie Ding, Yaya Shi, Cheng.Feng, Huihui Xiao, Bin Wen, Fan Yang, Tingting Gao, Di Zhang TD-Paint: Faster Diffusion Inpainting Through Time-Aware Pixel Conditioning
Tsiry Mayet, Pourya Shamsolmoali, Simon Bernard, Eric Granger, Romain Hérault, Clement Chatelain Teaching Human Behavior Improves Content Understanding Abilities of VLMs
Somesh Kumar Singh, S I Harini, Yaman Kumar Singla, Changyou Chen, Rajiv Ratn Shah, Veeky Baths, Balaji Krishnamurthy Teaching LLMs How to Learn with Contextual Fine-Tuning
Younwoo Choi, Muhammad Adil Asif, Ziwen Han, John Willes, Rahul Krishnan TeaserGen: Generating Teasers for Long Documentaries
Weihan Xu, Paul Pu Liang, Haven Kim, Julian McAuley, Taylor Berg-Kirkpatrick, Hao-Wen Dong Tell Me About Yourself: LLMs Are Aware of Their Learned Behaviors
Jan Betley, Xuchan Bao, Martín Soto, Anna Sztyber-Betley, James Chua, Owain Evans TempMe: Video Temporal Token Merging for Efficient Text-Video Retrieval
Leqi Shen, Tianxiang Hao, Tao He, Sicheng Zhao, Yifeng Zhang, Pengzhang Liu, Yongjun Bao, Guiguang Ding Temporal Reasoning Transfer from Text to Video
Lei Li, Yuanxin Liu, Linli Yao, Peiyuan Zhang, Chenxin An, Lean Wang, Xu Sun, Lingpeng Kong, Qi Liu TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data
Jeremy Andrew Irvin, Emily Ruoyu Liu, Joyce C. Chen, Ines Dormoy, Jinyoung Kim, Samar Khanna, Zhuo Zheng, Stefano Ermon Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning
Bahare Fatemi, Mehran Kazemi, Anton Tsitsulin, Karishma Malkan, Jinyeong Yim, John Palowitch, Sungyong Seo, Jonathan Halcrow, Bryan Perozzi Test-Time Adaptation for Cross-Modal Retrieval with Query Shift
Haobin Li, Peng Hu, Qianjun Zhang, Xi Peng, XitingLiu, Mouxing Yang Test-Time Adaptation for Image Compression with Distribution Regularization
Kecheng Chen, Pingping Zhang, Tiexin Qin, Shiqi Wang, Hong Yan, Haoliang Li Test-Time Adaptation for Regression by Subspace Alignment
Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai, Tomoki Hamagami Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation
Byungjai Kim, Chanho Ahn, Wissam J. Baddar, Kikyung Kim, Huijin Lee, Saehyun Ahn, Seungju Han, Sungjoo Suh, Eunho Yang Text-to-Image Rectified Flow as Plug-and-Play Priors
Xiaofeng Yang, Chen Cheng, Xulei Yang, Fayao Liu, Guosheng Lin Text2PDE: Latent Diffusion Models for Accessible Physics Simulation
Anthony Zhou, Zijie Li, Michael Schneier, John R Buchanan Jr, Amir Barati Farimani Text4Seg: Reimagining Image Segmentation as Text Generation
Mengcheng Lan, Chaofeng Chen, Yue Zhou, Jiaxing Xu, Yiping Ke, Xinjiang Wang, Litong Feng, Wayne Zhang TFG-Flow: Training-Free Guidance in Multimodal Generative Flow
Haowei Lin, Shanda Li, Haotian Ye, Yiming Yang, Stefano Ermon, Yitao Liang, Jianzhu Ma TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics
Lu Yi, Jie Peng, Yanping Zheng, Fengran Mo, Zhewei Wei, Yuhang Ye, Yue Zixuan, Zengfeng Huang The 3D-PC: A Benchmark for Visual Perspective Taking in Humans and Machines
Drew Linsley, Peisen Zhou, Alekh Karkada Ashok, Akash Nagaraj, Gaurav Gaonkar, Francis E Lewis, Zygmunt Pizlo, Thomas Serre The AdEMAMix Optimizer: Better, Faster, Older
Matteo Pagliardini, Pierre Ablin, David Grangier The Belief State Transformer
Edward S. Hu, Kwangjun Ahn, Qinghua Liu, Haoran Xu, Manan Tomar, Ada Langford, Dinesh Jayaraman, Alex Lamb, John Langford The Foundations of Tokenization: Statistical and Computational Concerns
Juan Luis Gastaldi, John Terilla, Luca Malagutti, Brian DuSell, Tim Vieira, Ryan Cotterell The Journey Matters: Average Parameter Count over Pre-Training Unifies Sparse and Dense Scaling Laws
Tian Jin, Ahmed Imtiaz Humayun, Utku Evci, Suvinay Subramanian, Amir Yazdanbakhsh, Dan Alistarh, Gintare Karolina Dziugaite The KoLMogorov Test: Compression by Code Generation
Ori Yoran, Kunhao Zheng, Fabian Gloeckle, Jonas Gehring, Gabriel Synnaeve, Taco Cohen The Labyrinth of Links: Navigating the Associative Maze of Multi-Modal LLMs
Hong Li, Nanxi Li, Yuanjie Chen, Jianbin Zhu, Qinlu Guo, Cewu Lu, Yong-Lu Li The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD
Milad Nasr, Thomas Steinke, Borja Balle, Christopher A. Choquette-Choo, Arun Ganesh, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis The OMG Dataset: An Open MetaGenomic Corpus for Mixed-Modality Genomic Language Modeling
Andre Cornman, Jacob West-Roberts, Antonio Pedro Camargo, Simon Roux, Martin Beracochea, Milot Mirdita, Sergey Ovchinnikov, Yunha Hwang The Optimization Landscape of SGD Across the Feature Learning Strength
Alexander Atanasov, Alexandru Meterez, James B Simon, Cengiz Pehlevan The Pitfalls of Memorization: When Memorization Hurts Generalization
Reza Bayat, Mohammad Pezeshki, Elvis Dohmatob, David Lopez-Paz, Pascal Vincent The Superposition of Diffusion Models Using the Itô Density Estimator
Marta Skreta, Lazar Atanackovic, Joey Bose, Alexander Tong, Kirill Neklyudov The Unreasonable Ineffectiveness of the Deeper Layers
Andrey Gromov, Kushal Tirumala, Hassan Shapourian, Paolo Glorioso, Dan Roberts The Value of Sensory Information to a Robot
Arjun Krishna, Edward S. Hu, Dinesh Jayaraman Theory on Mixture-of-Experts in Continual Learning
Hongbo Li, Sen Lin, Lingjie Duan, Yingbin Liang, Ness Shroff Theory, Analysis, and Best Practices for Sigmoid Self-Attention
Jason Ramapuram, Federico Danieli, Eeshan Gunesh Dhekane, Floris Weers, Dan Busbridge, Pierre Ablin, Tatiana Likhomanenko, Jagrit Digani, Zijin Gu, Amitis Shidani, Russell Webb ThermalGaussian: Thermal 3D Gaussian Splatting
Rongfeng Lu, Hangyu Chen, Zunjie Zhu, Yuhang Qin, Ming Lu, Le Zhang, Chenggang Yan, Anke Xue Think Thrice Before You Act: Progressive Thought Refinement in Large Language Models
Chengyu Du, Jinyi Han, Yizhou Ying, Aili Chen, Qianyu He, Haokun Zhao, Haoran Guo, Sirui Xia, Jiaqing Liang, Zulong Chen, Liangyue Li, Yanghua Xiao Think While You Generate: Discrete Diffusion with Planned Denoising
Sulin Liu, Juno Nam, Andrew Campbell, Hannes Stark, Yilun Xu, Tommi Jaakkola, Rafael Gomez-Bombarelli ThinK: Thinner Key Cache by Query-Driven Pruning
Yuhui Xu, Zhanming Jie, Hanze Dong, Lei Wang, Xudong Lu, Aojun Zhou, Amrita Saha, Caiming Xiong, Doyen Sahoo ThunderKittens: Simple, Fast, and $\textit{Adorable}$ Kernels
Benjamin Frederick Spector, Simran Arora, Aaryan Singhal, Arjun Parthasarathy, Daniel Y Fu, Christopher Re TIGeR: Unifying Text-to-Image Generation and Retrieval with Large Multimodal Models
Leigang Qu, Haochuan Li, Tan Wang, Wenjie Wang, Yongqi Li, Liqiang Nie, Tat-Seng Chua Tight Clusters Make Specialized Experts
Stefan Nielsen, Rachel Teo, Laziz Abdullaev, Tan Minh Nguyen Time After Time: Deep-Q Effect Estimation for Interventions on When and What to Do
Yoav Wald, Mark Goldstein, Yonathan Efroni, Wouter A.C. van Amsterdam, Rajesh Ranganath Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
Xiaoming Shi, Shiyu Wang, Yuqi Nie, Dianqi Li, Zhou Ye, Qingsong Wen, Ming Jin Time-to-Event Pretraining for 3D Medical Imaging
Zepeng Frazier Huo, Jason Alan Fries, Alejandro Lozano, Jeya Maria Jose Valanarasu, Ethan Steinberg, Louis Blankemeier, Akshay S Chaudhari, Curtis Langlotz, Nigam Shah TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
Shiyu Wang, Jiawei Li, Xiaoming Shi, Zhou Ye, Baichuan Mo, Wenze Lin, Ju Shengtong, Zhixuan Chu, Ming Jin TimeSuite: Improving MLLMs for Long Video Understanding via Grounded Tuning
Xiangyu Zeng, Kunchang Li, Chenting Wang, Xinhao Li, Tianxiang Jiang, Ziang Yan, Songze Li, Yansong Shi, Zhengrong Yue, Yi Wang, Yali Wang, Yu Qiao, Limin Wang TIPS: Text-Image Pretraining with Spatial Awareness
Kevis-kokitsi Maninis, Kaifeng Chen, Soham Ghosh, Arjun Karpur, Koert Chen, Ye Xia, Bingyi Cao, Daniel Salz, Guangxing Han, Jan Dlabal, Dan Gnanapragasam, Mojtaba Seyedhosseini, Howard Zhou, Andre Araujo TIS-DPO: Token-Level Importance Sampling for Direct Preference Optimization with Estimated Weights
Aiwei Liu, Haoping Bai, Zhiyun Lu, Yanchao Sun, Xiang Kong, Xiaoming Simon Wang, Jiulong Shan, Albin Madappally Jose, Xiaojiang Liu, Lijie Wen, Philip S. Yu, Meng Cao TLDR: Token-Level Detective Reward Model for Large Vision Language Models
Deqing Fu, Tong Xiao, Rui Wang, Wang Zhu, Pengchuan Zhang, Guan Pang, Robin Jia, Lawrence Chen To Code or Not to Code? Exploring Impact of Code in Pre-Training
Viraat Aryabumi, Yixuan Su, Raymond Ma, Adrien Morisot, Ivan Zhang, Acyr Locatelli, Marzieh Fadaee, Ahmet Üstün, Sara Hooker To CoT or Not to CoT? Chain-of-Thought Helps Mainly on Math and Symbolic Reasoning
Zayne Rea Sprague, Fangcong Yin, Juan Diego Rodriguez, Dongwei Jiang, Manya Wadhwa, Prasann Singhal, Xinyu Zhao, Xi Ye, Kyle Mahowald, Greg Durrett ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge
Eslam Mohamed Bakr, Liangbing Zhao, Vincent Tao Hu, Matthieu Cord, Patrick Perez, Mohamed Elhoseiny Token Statistics Transformer: Linear-Time Attention via Variational Rate Reduction
Ziyang Wu, Tianjiao Ding, Yifu Lu, Druv Pai, Jingyuan Zhang, Weida Wang, Yaodong Yu, Yi Ma, Benjamin David Haeffele TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters
Haiyang Wang, Yue Fan, Muhammad Ferjad Naeem, Yongqin Xian, Jan Eric Lenssen, Liwei Wang, Federico Tombari, Bernt Schiele TOMATO: Assessing Visual Temporal Reasoning Capabilities in Multimodal Foundation Models
Ziyao Shangguan, Chuhan Li, Yuxuan Ding, Yanan Zheng, Yilun Zhao, Tesca Fitzgerald, Arman Cohan Tool-Planner: Task Planning with Clusters Across Multiple Tools
Yanming Liu, Xinyue Peng, Jiannan Cao, Shi Bo, Yuwei Zhang, Xuhong Zhang, Sheng Cheng, Xun Wang, Jianwei Yin, Tianyu Du ToolACE: Winning the Points of LLM Function Calling
Weiwen Liu, Xu Huang, Xingshan Zeng, Xinlong Hao, Shuai Yu, Dexun Li, Shuai Wang, Weinan Gan, Zhengying Liu, Yuanqing Yu, Zezhong Wang, Yuxian Wang, Wu Ning, Yutai Hou, Bin Wang, Chuhan Wu, Wang Xinzhi, Yong Liu, Yasheng Wang, Duyu Tang, Dandan Tu, Lifeng Shang, Xin Jiang, Ruiming Tang, Defu Lian, Qun Liu, Enhong Chen ToolGen: Unified Tool Retrieval and Calling via Generation
Renxi Wang, Xudong Han, Lei Ji, Shu Wang, Timothy Baldwin, Haonan Li TOP-ERL: Transformer-Based Off-Policy Episodic Reinforcement Learning
Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov, Gerhard Neumann TopoGaussian: Inferring Internal Topology Structures from Visual Clues
Xiaoyu Xiong, Changyu Hu, Chunru Lin, Pingchuan Ma, Chuang Gan, Tao Du Topograph: An Efficient Graph-Based Framework for Strictly Topology Preserving Image Segmentation
Laurin Lux, Alexander H Berger, Alexander Weers, Nico Stucki, Daniel Rueckert, Ulrich Bauer, Johannes C. Paetzold TopoLM: Brain-like Spatio-Functional Organization in a Topographic Language Model
Neil Rathi, Johannes Mehrer, Badr AlKhamissi, Taha Osama A Binhuraib, Nicholas Blauch, Martin Schrimpf TorchTitan: One-Stop PyTorch Native Solution for Production Ready LLM Pretraining
Wanchao Liang, Tianyu Liu, Less Wright, Will Constable, Andrew Gu, Chien-Chin Huang, Iris Zhang, Wei Feng, Howard Huang, Junjie Wang, Sanket Purandare, Gokul Nadathur, Stratos Idreos Toward Understanding In-Context vs. In-Weight Learning
Bryan Chan, Xinyi Chen, András György, Dale Schuurmans Towards Calibrated Deep Clustering Network
Yuheng Jia, Jianhong Cheng, Hui Liu, Junhui Hou Towards Certification of Uncertainty Calibration Under Adversarial Attacks
Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz, Philip Torr, Adel Bibi Towards Counterfactual Fairness Through Auxiliary Variables
Bowei Tian, Ziyao Wang, Shwai He, Wanghao Ye, Guoheng Sun, Yucong Dai, Yongkai Wu, Ang Li Towards Effective Evaluations and Comparisons for LLM Unlearning Methods
Qizhou Wang, Bo Han, Puning Yang, Jianing Zhu, Tongliang Liu, Masashi Sugiyama Towards Federated RLHF with Aggregated Client Preference for LLMs
Feijie Wu, Xiaoze Liu, Haoyu Wang, Xingchen Wang, Lu Su, Jing Gao Towards Foundation Models for Mixed Integer Linear Programming
Sirui Li, Janardhan Kulkarni, Ishai Menache, Cathy Wu, Beibin Li Towards General-Purpose Model-Free Reinforcement Learning
Scott Fujimoto, Pierluca D'Oro, Amy Zhang, Yuandong Tian, Michael Rabbat Towards Hierarchical Rectified Flow
Yichi Zhang, Yici Yan, Alex Schwing, Zhizhen Zhao Towards Improving Exploration Through Sibling Augmented GFlowNets
Kanika Madan, Alex Lamb, Emmanuel Bengio, Glen Berseth, Yoshua Bengio Towards Learning High-Precision Least Squares Algorithms with Sequence Models
Jerry Weihong Liu, Jessica Grogan, Owen M Dugan, Ashish Rao, Simran Arora, Atri Rudra, Christopher Re Towards Multiple Character Image Animation Through Enhancing Implicit Decoupling
Jingyun Xue, Hongfa Wang, Qi Tian, Yue Ma, Andong Wang, Zhiyuan Zhao, Shaobo Min, Wenzhe Zhao, Kaihao Zhang, Heung-Yeung Shum, Wei Liu, Mengyang Liu, Wenhan Luo Towards Neural Scaling Laws for Time Series Foundation Models
Qingren Yao, Chao-Han Huck Yang, Renhe Jiang, Yuxuan Liang, Ming Jin, Shirui Pan Towards Optimal Multi-Draft Speculative Decoding
Zhengmian Hu, Tong Zheng, Vignesh Viswanathan, Ziyi Chen, Ryan A. Rossi, Yihan Wu, Dinesh Manocha, Heng Huang Towards Realistic Data Generation for Real-World Super-Resolution
Long Peng, Wenbo Li, Renjing Pei, Jingjing Ren, Jiaqi Xu, Yang Wang, Yang Cao, Zheng-Jun Zha Towards Realistic UAV Vision-Language Navigation: Platform, Benchmark, and Methodology
Xiangyu Wang, Donglin Yang, Ziqin Wang, Hohin Kwan, Jinyu Chen, Wenjun Wu, Hongsheng Li, Yue Liao, Si Liu Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization
Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning
Somnath Basu Roy Chowdhury, Krzysztof Marcin Choromanski, Arijit Sehanobish, Kumar Avinava Dubey, Snigdha Chaturvedi Towards Semantic Equivalence of Tokenization in Multimodal LLM
Shengqiong Wu, Hao Fei, Xiangtai Li, Jiayi Ji, Hanwang Zhang, Tat-Seng Chua, Shuicheng Yan Towards Synergistic Path-Based Explanations for Knowledge Graph Completion: Exploration and Evaluation
Tengfei Ma, Xiang Song, Wen Tao, Mufei Li, Jiani Zhang, Xiaoqin Pan, Yijun Wang, Bosheng Song, Xiangxiang Zeng TRACE: Temporal Grounding Video LLM via Causal Event Modeling
Yongxin Guo, Jingyu Liu, Mingda Li, Qingbin Liu, Xi Chen, Xiaoying Tang TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies
Ruijie Zheng, Yongyuan Liang, Shuaiyi Huang, Jianfeng Gao, Hal Daumé Iii, Andrey Kolobov, Furong Huang, Jianwei Yang Tracking Objects That Change in Appearance with Phase Synchrony
Sabine Muzellec, Drew Linsley, Alekh Karkada Ashok, Ennio Mingolla, Girik Malik, Rufin VanRullen, Thomas Serre Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
Jun Zhang, Jue Wang, Huan Li, Lidan Shou, Ke Chen, Yang You, Guiming Xie, Xuejian Gong, Kunlong Zhou Training Free Exponential Context Extension via Cascading KV Cache
Jeffrey Willette, Heejun Lee, Youngwan Lee, Myeongjae Jeon, Sung Ju Hwang Training Free Guided Flow-Matching with Optimal Control
Luran Wang, Chaoran Cheng, Yizhen Liao, Yanru Qu, Ge Liu Training Language Models to Self-Correct via Reinforcement Learning
Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal Behbahani, Aleksandra Faust Training Neural Networks as Recognizers of Formal Languages
Alexandra Butoi, Ghazal Khalighinejad, Anej Svete, Josef Valvoda, Ryan Cotterell, Brian DuSell Training-Free Activation Sparsity in Large Language Models
James Liu, Pragaash Ponnusamy, Tianle Cai, Han Guo, Yoon Kim, Ben Athiwaratkun Training-Free Message Passing for Learning on Hypergraphs
Bohan Tang, Zexi Liu, Keyue Jiang, Siheng Chen, Xiaowen Dong Trajectory Attention for Fine-Grained Video Motion Control
Zeqi Xiao, Wenqi Ouyang, Yifan Zhou, Shuai Yang, Lei Yang, Jianlou Si, Xingang Pan Trajectory-LLM: A Language-Based Data Generator for Trajectory Prediction in Autonomous Driving
Kairui Yang, Zihao Guo, Gengjie Lin, Haotian Dong, Zhao Huang, Yipeng Wu, Die Zuo, Jibin Peng, Ziyuan Zhong, Xin Wang, Qing Guo, Xiaosong Jia, Junchi Yan, Di Lin Transformers Are Universal In-Context Learners
Takashi Furuya, Maarten V. de Hoop, Gabriel Peyré Transformers Learn Low Sensitivity Functions: Investigations and Implications
Bhavya Vasudeva, Deqing Fu, Tianyi Zhou, Elliott Kau, Youqi Huang, Vatsal Sharan Transformers Struggle to Learn to Search
Abulhair Saparov, Srushti Ajay Pawar, Shreyas Pimpalgaonkar, Nitish Joshi, Richard Yuanzhe Pang, Vishakh Padmakumar, Mehran Kazemi, Najoung Kim, He He Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model
Chunting Zhou, Lili Yu, Arun Babu, Kushal Tirumala, Michihiro Yasunaga, Leonid Shamis, Jacob Kahn, Xuezhe Ma, Luke Zettlemoyer, Omer Levy Truncated Consistency Models
Sangyun Lee, Yilun Xu, Tomas Geffner, Giulia Fanti, Karsten Kreis, Arash Vahdat, Weili Nie TULIP: Token-Length Upgraded CLIP
Ivona Najdenkoska, Mohammad Mahdi Derakhshani, Yuki M Asano, Nanne Van Noord, Marcel Worring, Cees G. M. Snoek Tuning Frequency Bias of State Space Models
Annan Yu, Dongwei Lyu, Soon Hoe Lim, Michael W. Mahoney, N. Benjamin Erichson Tuning Timestep-Distilled Diffusion Model Using Pairwise Sample Optimization
Zichen Miao, Zhengyuan Yang, Kevin Lin, Ze Wang, Zicheng Liu, Lijuan Wang, Qiang Qiu Turning up the Heat: Min-P Sampling for Creative and Coherent LLM Outputs
Nguyen Nhat Minh, Andrew Baker, Clement Neo, Allen G Roush, Andreas Kirsch, Ravid Shwartz-Ziv U-$\mu$P: The Unit-Scaled Maximal Update Parametrization
Charlie Blake, Constantin Eichenberg, Josef Dean, Lukas Balles, Luke Yuri Prince, Björn Deiseroth, Andres Felipe Cruz-Salinas, Carlo Luschi, Samuel Weinbach, Douglas Orr Ultra-Sparse Memory Network
Zihao Huang, Qiyang Min, Hongzhi Huang, Yutao Zeng, Defa Zhu, Ran Guo, Zhou Xun Unbounded: A Generative Infinite Game of Character Life Simulation
Jialu Li, Yuanzhen Li, Neal Wadhwa, Yael Pritch, David E. Jacobs, Michael Rubinstein, Mohit Bansal, Nataniel Ruiz Uncertainty Modeling for Fine-Tuned Implicit Functions
Anna Susmelj, Mael Macuglia, Natasa Tagasovska, Reto Sutter, Sebastiano Caprara, Jean-Philippe Thiran, Ender Konukoglu Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
Richard Bergna, Sergio Calvo Ordoñez, Felix Opolka, Pietro Lio, José Miguel Hernández-Lobato Uncertainty-Aware Decoding with Minimum Bayes Risk
Nico Daheim, Clara Meister, Thomas Möllenhoff, Iryna Gurevych Uncovering Latent Memories in Large Language Models
Sunny Duan, Mikail Khona, Abhiram Iyer, Rylan Schaeffer, Ila R Fiete Uncovering Overfitting in Large Language Model Editing
Mengqi Zhang, Xiaotian Ye, Qiang Liu, Shu Wu, Pengjie Ren, Zhumin Chen Underdamped Diffusion Bridges with Applications to Sampling
Denis Blessing, Julius Berner, Lorenz Richter, Gerhard Neumann Understanding and Enhancing Safety Mechanisms of LLMs via Safety-Specific Neuron
Yiran Zhao, Wenxuan Zhang, Yuxi Xie, Anirudh Goyal, Kenji Kawaguchi, Michael Shieh Understanding Long Videos with Multimodal Language Models
Kanchana Ranasinghe, Xiang Li, Kumara Kahatapitiya, Michael S Ryoo Understanding Optimization in Deep Learning with Central Flows
Jeremy Cohen, Alex Damian, Ameet Talwalkar, J Zico Kolter, Jason D. Lee Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study
Xingxuan Zhang, Haoran Wang, Jiansheng Li, Yuan Xue, Shikai Guan, Renzhe Xu, Hao Zou, Han Yu, Peng Cui Understanding Virtual Nodes: Oversquashing and Node Heterogeneity
Joshua Southern, Francesco Di Giovanni, Michael M. Bronstein, Johannes F. Lutzeyer Understanding Warmup-Stable-Decay Learning Rates: A River Valley Loss Landscape View
Kaiyue Wen, Zhiyuan Li, Jason S. Wang, David Leo Wright Hall, Percy Liang, Tengyu Ma Unearthing Skill-Level Insights for Understanding Trade-Offs of Foundation Models
Mazda Moayeri, Vidhisha Balachandran, Varun Chandrasekaran, Safoora Yousefi, Thomas Fel, Soheil Feizi, Besmira Nushi, Neel Joshi, Vibhav Vineet Unhackable Temporal Reward for Scalable Video MLLMs
En Yu, Kangheng Lin, Liang Zhao, Yana Wei, Zining Zhu, Haoran Wei, Jianjian Sun, Zheng Ge, Xiangyu Zhang, Jingyu Wang, Wenbing Tao Uni-Sign: Toward Unified Sign Language Understanding at Scale
Zecheng Li, Wengang Zhou, Weichao Zhao, Kepeng Wu, Hezhen Hu, Houqiang Li UniCBE: An Uniformity-Driven Comparing Based Evaluation Framework with Unified Multi-Objective Optimization
Peiwen Yuan, Shaoxiong Feng, Yiwei Li, Xinglin Wang, Yueqi Zhang, Jiayi Shi, Chuyi Tan, Boyuan Pan, Yao Hu, Kan Li Unified Parameter-Efficient Unlearning for LLMs
Chenlu Ding, Jiancan Wu, Yancheng Yuan, Jinda Lu, Kai Zhang, Alex Su, Xiang Wang, Xiangnan He Unifying Causal Representation Learning with the Invariance Principle
Dingling Yao, Dario Rancati, Riccardo Cadei, Marco Fumero, Francesco Locatello UniGS: Unified Language-Image-3D Pretraining with Gaussian Splatting
Haoyuan Li, Zhou Yanpeng, Tao Tang, Jifei Song, Yihan Zeng, Michael Kampffmeyer, Hang Xu, Xiaodan Liang UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery
Ruifeng Li, Mingqian Li, Wei Liu, Yuhua Zhou, Xiangxin Zhou, Yuan Yao, Qiang Zhang, Hongyang Chen Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization
Noam Razin, Sadhika Malladi, Adithya Bhaskar, Danqi Chen, Sanjeev Arora, Boris Hanin Union-over-Intersections: Object Detection Beyond Winner-Takes-All
Aritra Bhowmik, Pascal Mettes, Martin R. Oswald, Cees G. M. Snoek UniRestore3D: A Scalable Framework for General Shape Restoration
Yuang Wang, Yujian Zhang, Sida Peng, Xingyi He, Haoyu Guo, Yujun Shen, Hujun Bao, Xiaowei Zhou UniWav: Towards Unified Pre-Training for Speech Representation Learning and Generation
Alexander H. Liu, Sang-gil Lee, Chao-Han Huck Yang, Yuan Gong, Yu-Chiang Frank Wang, James R. Glass, Rafael Valle, Bryan Catanzaro Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy
Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang Unlearning-Based Neural Interpretations
Ching Lam Choi, Alexandre Duplessis, Serge Belongie Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning
Tianci Liu, Ruirui Li, Yunzhe Qi, Hui Liu, Xianfeng Tang, Tianqi Zheng, Qingyu Yin, Monica Xiao Cheng, Jun Huan, Haoyu Wang, Jing Gao Unlocking Guidance for Discrete State-Space Diffusion and Flow Models
Hunter Nisonoff, Junhao Xiong, Stephan Allenspach, Jennifer Listgarten Unlocking Point Processes Through Point Set Diffusion
David Lüdke, Enric Rabasseda Raventós, Marcel Kollovieh, Stephan Günnemann Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues
Riccardo Grazzi, Julien Siems, Arber Zela, Jörg K.H. Franke, Frank Hutter, Massimiliano Pontil Unlocking the Potential of Model Calibration in Federated Learning
Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour, Christopher Brinton Unsupervised Meta-Learning via In-Context Learning
Anna Vettoruzzo, Lorenzo Braccaioli, Joaquin Vanschoren, Marlena Nowaczyk Unsupervised Zero-Shot Reinforcement Learning via Dual-Value Forward-Backward Representation
Jingbo Sun, Songjun Tu, Qichao Zhang, Haoran Li, Xin Liu, Yaran Chen, Ke Chen, Dongbin Zhao Unveiling the Magic of Code Reasoning Through Hypothesis Decomposition and Amendment
Yuze Zhao, Tianyun Ji, Wenjun Feng, Zhenya Huang, Qi Liu, Zhiding Liu, Yixiao Ma, Kai Zhang, Enhong Chen Unveiling the Secret Recipe: A Guide for Supervised Fine-Tuning Small LLMs
Aldo Pareja, Nikhil Shivakumar Nayak, Hao Wang, Krishnateja Killamsetty, Shivchander Sudalairaj, Wenlong Zhao, Seungwook Han, Abhishek Bhandwaldar, Guangxuan Xu, Kai Xu, Ligong Han, Luke Inglis, Akash Srivastava Valid Conformal Prediction for Dynamic GNNs
Ed Davis, Ian Gallagher, Daniel John Lawson, Patrick Rubin-Delanchy Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF
Shicong Cen, Jincheng Mei, Katayoon Goshvadi, Hanjun Dai, Tong Yang, Sherry Yang, Dale Schuurmans, Yuejie Chi, Bo Dai Variance-Reducing Couplings for Random Features
Isaac Reid, Stratis Markou, Krzysztof Marcin Choromanski, Richard E. Turner, Adrian Weller Variational Bayesian Pseudo-Coreset
Hyungi Lee, Seungyoo Lee, Juho Lee Variational Best-of-N Alignment
Afra Amini, Tim Vieira, Elliott Ash, Ryan Cotterell Variational Diffusion Posterior Sampling with Midpoint Guidance
Badr Moufad, Yazid Janati, Lisa Bedin, Alain Oliviero Durmus, Randal Douc, Eric Moulines, Jimmy Olsson Variational Search Distributions
Daniel M. Steinberg, Rafael Oliveira, Cheng Soon Ong, Edwin V. Bonilla Varying Shades of Wrong: Aligning LLMs with Wrong Answers Only
Jihan Yao, Wenxuan Ding, Shangbin Feng, Lucy Lu Wang, Yulia Tsvetkov VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text
Tianyu Zhang, Suyuchen Wang, Lu Li, Ge Zhang, Perouz Taslakian, Sai Rajeswar, Jie Fu, Bang Liu, Yoshua Bengio VD3D: Taming Large Video Diffusion Transformers for 3D Camera Control
Sherwin Bahmani, Ivan Skorokhodov, Aliaksandr Siarohin, Willi Menapace, Guocheng Qian, Michael Vasilkovsky, Hsin-Ying Lee, Chaoyang Wang, Jiaxu Zou, Andrea Tagliasacchi, David B. Lindell, Sergey Tulyakov VEDIT: Latent Prediction Architecture for Procedural Video Representation Learning
Han Lin, Tushar Nagarajan, Nicolas Ballas, Mido Assran, Mojtaba Komeili, Mohit Bansal, Koustuv Sinha Vevo: Controllable Zero-Shot Voice Imitation with Self-Supervised Disentanglement
Xueyao Zhang, Xiaohui Zhang, Kainan Peng, Zhenyu Tang, Vimal Manohar, Yingru Liu, Jeff Hwang, Dangna Li, Yuhao Wang, Julian Chan, Yuan Huang, Zhizheng Wu, Mingbo Ma VibeCheck: Discover and Quantify Qualitative Differences in Large Language Models
Lisa Dunlap, Krishna Mandal, Trevor Darrell, Jacob Steinhardt, Joseph E. Gonzalez Video Action Differencing
James Burgess, Xiaohan Wang, Yuhui Zhang, Anita Rau, Alejandro Lozano, Lisa Dunlap, Trevor Darrell, Serena Yeung-Levy VideoPhy: Evaluating Physical Commonsense for Video Generation
Hritik Bansal, Zongyu Lin, Tianyi Xie, Zeshun Zong, Michal Yarom, Yonatan Bitton, Chenfanfu Jiang, Yizhou Sun, Kai-Wei Chang, Aditya Grover VideoWebArena: Evaluating Long Context Multimodal Agents with Video Understanding Web Tasks
Lawrence Keunho Jang, Yinheng Li, Dan Zhao, Charles Ding, Justin Lin, Paul Pu Liang, Rogerio Bonatti, Kazuhito Koishida ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation
Tianchen Zhao, Tongcheng Fang, Haofeng Huang, Rui Wan, Widyadewi Soedarmadji, Enshu Liu, Shiyao Li, Zinan Lin, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning, Yu Wang VILA-U: A Unified Foundation Model Integrating Visual Understanding and Generation
Yecheng Wu, Zhuoyang Zhang, Junyu Chen, Haotian Tang, Dacheng Li, Yunhao Fang, Ligeng Zhu, Enze Xie, Hongxu Yin, Li Yi, Song Han, Yao Lu Vision and Language Synergy for Rehearsal Free Continual Learning
Muhammad Anwar Ma'sum, Mahardhika Pratama, Savitha Ramasamy, Lin Liu, H Habibullah, Ryszard Kowalczyk Vision Language Models Are In-Context Value Learners
Yecheng Jason Ma, Joey Hejna, Chuyuan Fu, Dhruv Shah, Jacky Liang, Zhuo Xu, Sean Kirmani, Peng Xu, Danny Driess, Ted Xiao, Osbert Bastani, Dinesh Jayaraman, Wenhao Yu, Tingnan Zhang, Dorsa Sadigh, Fei Xia Vision-LSTM: xLSTM as Generic Vision Backbone
Benedikt Alkin, Maximilian Beck, Korbinian Pöppel, Sepp Hochreiter, Johannes Brandstetter Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-like Architectures
Yuchen Duan, Weiyun Wang, Zhe Chen, Xizhou Zhu, Lewei Lu, Tong Lu, Yu Qiao, Hongsheng Li, Jifeng Dai, Wenhai Wang VisRAG: Vision-Based Retrieval-Augmented Generation on Multi-Modality Documents
Shi Yu, Chaoyue Tang, Bokai Xu, Junbo Cui, Junhao Ran, Yukun Yan, Zhenghao Liu, Shuo Wang, Xu Han, Zhiyuan Liu, Maosong Sun Visual Agents as Fast and Slow Thinkers
Guangyan Sun, Mingyu Jin, Zhenting Wang, Cheng-Long Wang, Siqi Ma, Qifan Wang, Tong Geng, Ying Nian Wu, Yongfeng Zhang, Dongfang Liu Visual Description Grounding Reduces Hallucinations and Boosts Reasoning in LVLMs
Sreyan Ghosh, Chandra Kiran Reddy Evuru, Sonal Kumar, Utkarsh Tyagi, Oriol Nieto, Zeyu Jin, Dinesh Manocha Visual Haystacks: A Vision-Centric Needle-in-a-Haystack Benchmark
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