ICML 2025
3330 papers
"Why Is There a Tumor?": Tell Me the Reason, Show Me the Evidence
Mengmeng Ma, Tang Li, Yunxiang Peng, Lu Lin, Volkan Beylergil, Binsheng Zhao, Oguz Akin, Xi Peng (How) Can Transformers Predict Pseudo-Random Numbers?
Tao Tao, Darshil Doshi, Dayal Singh Kalra, Tianyu He, Maissam Barkeshli (How) Do Language Models Track State?
Belinda Z. Li, Zifan Carl Guo, Jacob Andreas $\mathrmμ$nit Scaling: Simple and Scalable FP8 LLM Training
Saaketh Narayan, Abhay Gupta, Mansheej Paul, Davis Blalock $\texttt{I}$^2$MoE$: Interpretable Multimodal Interaction-Aware Mixture-of-Experts
Jiayi Xin, Sukwon Yun, Jie Peng, Inyoung Choi, Jenna L. Ballard, Tianlong Chen, Qi Long $S^2$FGL: Spatial Spectral Federated Graph Learning
Zihan Tan, Suyuan Huang, Guancheng Wan, Wenke Huang, He Li, Mang Ye 3D Question Answering via Only 2D Vision-Language Models
Fengyun Wang, Sicheng Yu, Jiawei Wu, Jinhui Tang, Hanwang Zhang, Qianru Sun A Bregman Proximal Viewpoint on Neural Operators
Abdel-Rahim Mezidi, Jordan Patracone, Saverio Salzo, Amaury Habrard, Massimiliano Pontil, Rémi Emonet, Marc Sebban A Certified Unlearning Approach Without Access to Source Data
Umit Yigit Basaran, Sk Miraj Ahmed, Amit Roy-Chowdhury, Basak Guler A Classification View on Meta Learning Bandits
Mirco Mutti, Jeongyeol Kwon, Shie Mannor, Aviv Tamar A Closer Look at Backdoor Attacks on CLIP
Shuo He, Zhifang Zhang, Feng Liu, Roy Ka-Wei Lee, Bo An, Lei Feng A Closer Look at Multimodal Representation Collapse
Abhra Chaudhuri, Anjan Dutta, Tu Bui, Serban Georgescu A Cognac Shot to Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
Varshita Kolipaka, Akshit Sinha, Debangan Mishra, Sumit Kumar, Arvindh Arun, Shashwat Goel, Ponnurangam Kumaraguru A First-Order Generative Bilevel Optimization Framework for Diffusion Models
Quan Xiao, Hui Yuan, A F M Saif, Gaowen Liu, Ramana Rao Kompella, Mengdi Wang, Tianyi Chen A General Framework for Inference-Time Scaling and Steering of Diffusion Models
Raghav Singhal, Zachary Horvitz, Ryan Teehan, Mengye Ren, Zhou Yu, Kathleen Mckeown, Rajesh Ranganath A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition
Nian Liu, Xiaoxin He, Thomas Laurent, Francesco Di Giovanni, Michael M. Bronstein, Xavier Bresson A Large Recurrent Action Model: xLSTM Enables Fast Inference for Robotics Tasks
Thomas Schmied, Thomas Adler, Vihang Prakash Patil, Maximilian Beck, Korbinian Pöppel, Johannes Brandstetter, Günter Klambauer, Razvan Pascanu, Sepp Hochreiter A Mixture-Based Framework for Guiding Diffusion Models
Yazid Janati, Badr Moufad, Mehdi Abou El Qassime, Alain Oliviero Durmus, Eric Moulines, Jimmy Olsson A Model of Place Field Reorganization During Reward Maximization
M Ganesh Kumar, Blake Bordelon, Jacob A Zavatone-Veth, Cengiz Pehlevan A Physics-Augmented Deep Learning Framework for Classifying Single Molecule Force Spectroscopy Data
Cailong Hua, Sivaraman Rajaganapathy, Rebecca A Slick, Joseph Vavra, Joseph M. Muretta, James M. Ervasti, Murti Salapaka A Sample Efficient Conditional Independence Test in the Presence of Discretization
Boyang Sun, Yu Yao, Xinshuai Dong, Zongfang Liu, Tongliang Liu, Yumou Qiu, Kun Zhang A Theoretical Framework for Overfitting in Energy-Based Modeling
Giovanni Catania, Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane A Two-Stage Learning-to-Defer Approach for Multi-Task Learning
Yannis Montreuil, Yeo Shu Heng, Axel Carlier, Lai Xing Ng, Wei Tsang Ooi A Variational Framework for Improving Naturalness in Generative Spoken Language Models
Li-Wei Chen, Takuya Higuchi, Zakaria Aldeneh, Ahmed Hussen Abdelaziz, Alexander Rudnicky A Variational Perspective on Generative Protein Fitness Optimization
Lea Bogensperger, Dominik Narnhofer, Ahmed Allam, Konrad Schindler, Michael Krauthammer AAAR-1.0: Assessing AI’s Potential to Assist Research
Renze Lou, Hanzi Xu, Sijia Wang, Jiangshu Du, Ryo Kamoi, Xiaoxin Lu, Jian Xie, Yuxuan Sun, Yusen Zhang, Jihyun Janice Ahn, Hongchao Fang, Zhuoyang Zou, Wenchao Ma, Xi Li, Kai Zhang, Congying Xia, Lifu Huang, Wenpeng Yin Accelerated Diffusion Models via Speculative Sampling
Valentin De Bortoli, Alexandre Galashov, Arthur Gretton, Arnaud Doucet Accelerating Large Language Model Reasoning via Speculative Search
Zhihai Wang, Jie Wang, Jilai Pan, Xilin Xia, Huiling Zhen, Mingxuan Yuan, Jianye Hao, Feng Wu Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck, Philipp Stratmann, Andreas Wild, Sumit Bam Shrestha Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies
Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Gaurav Jain, Oren Pereg, Moshe Wasserblat, David Harel Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
Ze Cheng, Zhuoyu Li, Wang Xiaoqiang, Jianing Huang, Zhizhou Zhang, Zhongkai Hao, Hang Su Accelerating Spectral Clustering Under Fairness Constraints
Francesco Tonin, Alex Lambert, Johan Suykens, Volkan Cevher Action Dubber: Timing Audible Actions via Inflectional Flow
Wenlong Wan, Weiying Zheng, Tianyi Xiang, Guiqing Li, Shengfeng He Action-Constrained Imitation Learning
Chia-Han Yeh, Tse-Sheng Nan, Risto Vuorio, Wei Hung, Hung Yen Wu, Shao-Hua Sun, Ping-Chun Hsieh Action-Dependent Optimality-Preserving Reward Shaping
Grant Collier Forbes, Jianxun Wang, Leonardo Villalobos-Arias, Arnav Jhala, David Roberts ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation
Yupeng Hou, Jianmo Ni, Zhankui He, Noveen Sachdeva, Wang-Cheng Kang, Ed H. Chi, Julian Mcauley, Derek Zhiyuan Cheng Activation Space Interventions Can Be Transferred Between Large Language Models
Narmeen Fatimah Oozeer, Dhruv Nathawani, Nirmalendu Prakash, Michael Lan, Abir Harrasse, Amir Abdullah Active Evaluation Acquisition for Efficient LLM Benchmarking
Yang Li, Jie Ma, Miguel Ballesteros, Yassine Benajiba, Graham Horwood Active Feature Acquisition via Explainability-Driven Ranking
Osman Berke Guney, Ketan Suhaas Saichandran, Karim Elzokm, Ziming Zhang, Vijaya B Kolachalama Active Fine-Tuning of Multi-Task Policies
Marco Bagatella, Jonas Hübotter, Georg Martius, Andreas Krause Active Treatment Effect Estimation via Limited Samples
Zhiheng Zhang, Haoxiang Wang, Haoxuan Li, Zhouchen Lin Ad-Hoc Human-AI Coordination Challenge
Tin Dizdarević, Ravi Hammond, Tobias Gessler, Anisoara Calinescu, Jonathan Cook, Matteo Gallici, Andrei Lupu, Jakob Nicolaus Foerster Adapting Precomputed Features for Efficient Graph Condensation
Yuan Li, Jun Hu, Zemin Liu, Bryan Hooi, Jia Chen, Bingsheng He Adapting to Evolving Adversaries with Regularized Continual Robust Training
Sihui Dai, Christian Cianfarani, Vikash Sehwag, Prateek Mittal, Arjun Bhagoji Adaptive Data Collection for Robust Learning Across Multiple Distributions
Chengbo Zang, Mehmet Kerem Turkcan, Gil Zussman, Zoran Kostic, Javad Ghaderi Adaptive Estimation and Learning Under Temporal Distribution Shift
Dheeraj Baby, Yifei Tang, Hieu Duy Nguyen, Yu-Xiang Wang, Rohit Pyati Adaptive Flow Matching for Resolving Small-Scale Physics
Stathi Fotiadis, Noah D Brenowitz, Tomas Geffner, Yair Cohen, Michael Pritchard, Arash Vahdat, Morteza Mardani Adaptive Localization of Knowledge Negation for Continual LLM Unlearning
Abudukelimu Wuerkaixi, Qizhou Wang, Sen Cui, Wutong Xu, Bo Han, Gang Niu, Masashi Sugiyama, Changshui Zhang Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
Federico Errica, Henrik Christiansen, Viktor Zaverkin, Takashi Maruyama, Mathias Niepert, Francesco Alesiani Adaptive Sensitivity Analysis for Robust Augmentation Against Natural Corruptions in Image Segmentation
Laura Yu Zheng, Wenjie Wei, Tony Wu, Jacob Clements, Shreelekha Revankar, Andre Harrison, Yu Shen, Ming Lin AdaptiveStep: Automatically Dividing Reasoning Step Through Model Confidence
Yuliang Liu, Junjie Lu, Chaofeng Qu, Zhaoling Chen, Zefan Cai, Jason Klein Liu, Chonghan Liu, Yunhui Xia, Li Zhao, Jiang Bian, Chuheng Zhang, Wei Shen, Zhouhan Lin AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl AdaSplash: Adaptive Sparse Flash Attention
Nuno Gonçalves, Marcos V Treviso, Andre Martins ADDQ: Adaptive Distributional Double Q-Learning
Leif Döring, Benedikt Wille, Maximilian Birr, Mihail Bı̂rsan, Martin Slowik Addressing Misspecification in Simulation-Based Inference Through Data-Driven Calibration
Antoine Wehenkel, Juan L. Gamella, Ozan Sener, Jens Behrmann, Guillermo Sapiro, Joern-Henrik Jacobsen, Marco Cuturi ADHMR: Aligning Diffusion-Based Human Mesh Recovery via Direct Preference Optimization
Wenhao Shen, Wanqi Yin, Xiaofeng Yang, Cheng Chen, Chaoyue Song, Zhongang Cai, Lei Yang, Hao Wang, Guosheng Lin ADIOS: Antibody Development via Opponent Shaping
Sebastian Rene Towers, Aleksandra Kalisz, Philippe A. Robert, Alicia Higueruelo, Francesca Vianello, Chloe Ming-Han Tsai, Harrison Steel, Jakob Nicolaus Foerster Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
Aaron J Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Daniel S. Levine, Brandon M Wood, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen AdvAgent: Controllable Blackbox Red-Teaming on Web Agents
Chejian Xu, Mintong Kang, Jiawei Zhang, Zeyi Liao, Lingbo Mo, Mengqi Yuan, Huan Sun, Bo Li Advancing Personalized Learning with Neural Collapse for Long-Tail Challenge
Hanglei Hu, Yingying Guo, Zhikang Chen, Sen Cui, Fei Wu, Kun Kuang, Min Zhang, Bo Jiang Adversarial Inputs for Linear Algebra Backends
Jonas Möller, Lukas Pirch, Felix Weissberg, Sebastian Baunsgaard, Thorsten Eisenhofer, Konrad Rieck Adversarial Reasoning at Jailbreaking Time
Mahdi Sabbaghi, Paul Kassianik, George J. Pappas, Amin Karbasi, Hamed Hassani AdvI2I: Adversarial Image Attack on Image-to-Image Diffusion Models
Yaopei Zeng, Yuanpu Cao, Bochuan Cao, Yurui Chang, Jinghui Chen, Lu Lin AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs
Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, Yuandong Tian AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models
Zheng Lian, Haoyu Chen, Lan Chen, Haiyang Sun, Licai Sun, Yong Ren, Zebang Cheng, Bin Liu, Rui Liu, Xiaojiang Peng, Jiangyan Yi, Jianhua Tao AffinityFlow: Guided Flows for Antibody Affinity Maturation
Can Chen, Karla-Luise Herpoldt, Chenchao Zhao, Zichen Wang, Marcus D. Collins, Shang Shang, Ron Benson Agent Workflow Memory
Zora Zhiruo Wang, Jiayuan Mao, Daniel Fried, Graham Neubig Agent-as-a-Judge: Evaluate Agents with Agents
Mingchen Zhuge, Changsheng Zhao, Dylan R. Ashley, Wenyi Wang, Dmitrii Khizbullin, Yunyang Xiong, Zechun Liu, Ernie Chang, Raghuraman Krishnamoorthi, Yuandong Tian, Yangyang Shi, Vikas Chandra, Jürgen Schmidhuber Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction
Yiheng Xu, Zekun Wang, Junli Wang, Dunjie Lu, Tianbao Xie, Amrita Saha, Doyen Sahoo, Tao Yu, Caiming Xiong AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N
Tianyu Zhang, Andrew Robert Williams, Phillip Wozny, Kai-Hendrik Cohrs, Koen Ponse, Marco Jiralerspong, Soham Rajesh Phade, Sunil Srinivasa, Lu Li, Yang Zhang, Prateek Gupta, Erman Acar, Irina Rish, Yoshua Bengio, Stephan Zheng Alberta Wells Dataset: Pinpointing Oil and Gas Wells from Satellite Imagery
Pratinav Seth, Michelle Lin, Brefo Dwamena Yaw, Jade Boutot, Mary Kang, David Rolnick Algorithmic Recourse for Long-Term Improvement
Kentaro Kanamori, Ken Kobayashi, Satoshi Hara, Takuya Takagi Algorithms and Hardness for Active Learning on Graphs
Vincent Cohen-Addad, Silvio Lattanzi, Simon Meierhans Aligned Multi Objective Optimization
Yonathan Efroni, Ben Kretzu, Daniel R. Jiang, Jalaj Bhandari, Zheqing Zhu, Karen Ullrich Aligning LLMs by Predicting Preferences from User Writing Samples
Stéphane Aroca-Ouellette, Natalie Mackraz, Barry-John Theobald, Katherine Metcalf Aligning Multimodal Representations Through an Information Bottleneck
Antonio Almudévar, José Miguel Hernández-Lobato, Sameer Khurana, Ricard Marxer, Alfonso Ortega Aligning Protein Conformation Ensemble Generation with Physical Feedback
Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Aurelie Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang Aligning Spoken Dialogue Models from User Interactions
Anne Wu, Laurent Mazaré, Neil Zeghidour, Alexandre Défossez All-Atom Diffusion Transformers: Unified Generative Modelling of Molecules and Materials
Chaitanya K. Joshi, Xiang Fu, Yi-Lun Liao, Vahe Gharakhanyan, Benjamin Kurt Miller, Anuroop Sriram, Zachary Ward Ulissi Almost Optimal Fully Dynamic $k$-Center Clustering with Recourse
Sayan Bhattacharya, Martin Costa, Ermiya Farokhnejad, Silvio Lattanzi, Nikos Parotsidis ALMTokenizer: A Low-Bitrate and Semantic-Rich Audio Codec Tokenizer for Audio Language Modeling
Dongchao Yang, Songxiang Liu, Haohan Guo, Jiankun Zhao, Yuanyuan Wang, Helin Wang, Zeqian Ju, Xubo Liu, Xueyuan Chen, Xu Tan, Xixin Wu, Helen M. Meng Alpha-SQL: Zero-Shot Text-to-SQL Using Monte Carlo Tree Search
Boyan Li, Jiayi Zhang, Ju Fan, Yanwei Xu, Chong Chen, Nan Tang, Yuyu Luo AlphaDPO: Adaptive Reward Margin for Direct Preference Optimization
Junkang Wu, Xue Wang, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He AlphaPO: Reward Shape Matters for LLM Alignment
Aman Gupta, Shao Tang, Qingquan Song, Sirou Zhu, Jiwoo Hong, Ankan Saha, Viral Gupta, Noah Lee, Eunki Kim, Siyu Zhu, Parag Agrawal, Natesh S. Pillai, Sathiya Keerthi Am-ELO: A Stable Framework for Arena-Based LLM Evaluation
Zirui Liu, Jiatong Li, Yan Zhuang, Qi Liu, Shuanghong Shen, Jie Ouyang, Mingyue Cheng, Shijin Wang AMPO: Active Multi Preference Optimization for Self-Play Preference Selection
Taneesh Gupta, Rahul Madhavan, Xuchao Zhang, Chetan Bansal, Saravan Rajmohan An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN Architectures
Thibaut Boissin, Franck Mamalet, Thomas Fel, Agustin Martin Picard, Thomas Massena, Mathieu Serrurier An All-Atom Generative Model for Designing Protein Complexes
Ruizhe Chen, Dongyu Xue, Xiangxin Zhou, Zaixiang Zheng, Xiangxiang Zeng, Quanquan Gu An Architecture Search Framework for Inference-Time Techniques
Jon Saad-Falcon, Adrian Gamarra Lafuente, Shlok Natarajan, Nahum Maru, Hristo Todorov, Etash Kumar Guha, E. Kelly Buchanan, Mayee F Chen, Neel Guha, Christopher Re, Azalia Mirhoseini An Efficient Private GPT Never Autoregressively Decodes
Zhengyi Li, Yue Guan, Kang Yang, Yu Feng, Ning Liu, Yu Yu, Jingwen Leng, Minyi Guo An Interpretable N-Gram Perplexity Threat Model for Large Language Model Jailbreaks
Valentyn Boreiko, Alexander Panfilov, Vaclav Voracek, Matthias Hein, Jonas Geiping AnyEdit: Edit Any Knowledge Encoded in Language Models
Houcheng Jiang, Junfeng Fang, Ningyu Zhang, Mingyang Wan, Guojun Ma, Xiang Wang, Xiangnan He, Tat-Seng Chua Approximate Forest Completion and Learning-Augmented Algorithms for Metric Minimum Spanning Trees
Nate Veldt, Thomas Stanley, Benjamin W Priest, Trevor Steil, Keita Iwabuchi, T.S. Jayram, Geoffrey Sanders Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models
Thomas Fel, Ekdeep Singh Lubana, Jacob S. Prince, Matthew Kowal, Victor Boutin, Isabel Papadimitriou, Binxu Wang, Martin Wattenberg, Demba E. Ba, Talia Konkle Are High-Quality AI-Generated Images More Difficult for Models to Detect?
Yao Xiao, Binbin Yang, Weiyan Chen, Jiahao Chen, Zijie Cao, Ziyi Dong, Xiangyang Ji, Liang Lin, Wei Ke, Pengxu Wei Are Large Brainwave Foundation Models Capable yet ? Insights from Fine-Tuning
Na Lee, Konstantinos Barmpas, Yannis Panagakis, Dimitrios Adamos, Nikolaos Laskaris, Stefanos Zafeiriou Are Large Language Models Ready for Multi-Turn Tabular Data Analysis?
Jinyang Li, Nan Huo, Yan Gao, Jiayi Shi, Yingxiu Zhao, Ge Qu, Bowen Qin, Yurong Wu, Xiaodong Li, Chenhao Ma, Jian-Guang Lou, Reynold Cheng Are Sparse Autoencoders Useful? a Case Study in Sparse Probing
Subhash Kantamneni, Joshua Engels, Senthooran Rajamanoharan, Max Tegmark, Neel Nanda ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior
Zhongweiyang Xu, Xulin Fan, Zhong-Qiu Wang, Xilin Jiang, Romit Roy Choudhury Arrow: Accelerator for Time Series Causal Discovery with Time Weaving
Yuanyuan Yao, Yuan Dong, Lu Chen, Kun Kuang, Ziquan Fang, Cheng Long, Yunjun Gao, Tianyi Li AssistanceZero: Scalably Solving Assistance Games
Cassidy Laidlaw, Eli Bronstein, Timothy Guo, Dylan Feng, Lukas Berglund, Justin Svegliato, Stuart Russell, Anca Dragan AtlasD: Automatic Local Symmetry Discovery
Manu Bhat, Jonghyun Park, Jianke Yang, Nima Dehmamy, Robin Walters, Rose Yu Attention-Level Speculation
Jack Cai, Ammar Vora, Randolph Zhang, Mark O’Connor, Mark C. Jeffrey Attributes Shape the Embedding Space of Face Recognition Models
Pierrick Leroy, Antonio Mastropietro, Marco Nurisso, Francesco Vaccarino Audio Flamingo 2: An Audio-Language Model with Long-Audio Understanding and Expert Reasoning Abilities
Sreyan Ghosh, Zhifeng Kong, Sonal Kumar, S Sakshi, Jaehyeon Kim, Wei Ping, Rafael Valle, Dinesh Manocha, Bryan Catanzaro Auditing $f$-Differential Privacy in One Run
Saeed Mahloujifar, Luca Melis, Kamalika Chaudhuri Auditing Prompt Caching in Language Model APIs
Chenchen Gu, Xiang Lisa Li, Rohith Kuditipudi, Percy Liang, Tatsunori Hashimoto AuPair: Golden Example Pairs for Code Repair
Aditi Mavalankar, Hassan Mansoor, Zita Marinho, Mariia Samsikova, Tom Schaul AutoCATE: End-to-End, Automated Treatment Effect Estimation
Toon Vanderschueren, Tim Verdonck, Mihaela Van Der Schaar, Wouter Verbeke AutoEval Done Right: Using Synthetic Data for Model Evaluation
Pierre Boyeau, Anastasios Nikolas Angelopoulos, Tianle Li, Nir Yosef, Jitendra Malik, Michael I. Jordan Autoformulation of Mathematical Optimization Models Using LLMs
Nicolás Astorga, Tennison Liu, Yuanzhang Xiao, Mihaela Van Der Schaar Automated Hypothesis Validation with Agentic Sequential Falsifications
Kexin Huang, Ying Jin, Ryan Li, Michael Y. Li, Emmanuel Candes, Jure Leskovec Automated Red Teaming with GOAT: The Generative Offensive Agent Tester
Maya Pavlova, Erik Brinkman, Krithika Iyer, Vı́tor Albiero, Joanna Bitton, Hailey Nguyen, Cristian Canton Ferrer, Ivan Evtimov, Aaron Grattafiori Automatically Identify and Rectify: Robust Deep Contrastive Multi-View Clustering in Noisy Scenarios
Xihong Yang, Siwei Wang, Fangdi Wang, Jiaqi Jin, Suyuan Liu, Yue Liu, En Zhu, Xinwang Liu, Yueming Jin Autonomy-of-Experts Models
Ang Lv, Ruobing Xie, Yining Qian, Songhao Wu, Xingwu Sun, Zhanhui Kang, Di Wang, Rui Yan AutoStep: Locally Adaptive Involutive MCMC
Tiange Liu, Nikola Surjanovic, Miguel Biron-Lattes, Alexandre Bouchard-Cote, Trevor Campbell Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts
Mateo Espinosa Zarlenga, Gabriele Dominici, Pietro Barbiero, Zohreh Shams, Mateja Jamnik AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders
Zhengxuan Wu, Aryaman Arora, Atticus Geiger, Zheng Wang, Jing Huang, Dan Jurafsky, Christopher D Manning, Christopher Potts Balanced Learning for Domain Adaptive Semantic Segmentation
Wangkai Li, Rui Sun, Bohao Liao, Zhaoyang Li, Tianzhu Zhang Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality
Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca Balancing Model Efficiency and Performance: Adaptive Pruner for Long-Tailed Data
Zhe Zhao, Haibin Wen, Pengkun Wang, Shuang Wang, Zhenkun Wang, Qingfu Zhang, Yang Wang BAME: Block-Aware Mask Evolution for Efficient N:M Sparse Training
Chenyi Yang, Wenjie Nie, Yuxin Zhang, Yuhang Wu, Xiawu Zheng, Guannan Jiang, Rongrong Ji BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms
Yunlong Hou, Fengzhuo Zhang, Cunxiao Du, Xuan Zhang, Jiachun Pan, Tianyu Pang, Chao Du, Vincent Tan, Zhuoran Yang BARK: A Fully Bayesian Tree Kernel for Black-Box Optimization
Toby Boyne, Jose Pablo Folch, Robert Matthew Lee, Behrang Shafei, Ruth Misener Batch List-Decodable Linear Regression via Higher Moments
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Sihan Liu, Thanasis Pittas BaxBench: Can LLMs Generate Correct and Secure Backends?
Mark Vero, Niels Mündler, Victor Chibotaru, Veselin Raychev, Maximilian Baader, Nikola Jovanović, Jingxuan He, Martin Vechev Bayesian Active Learning for Bivariate Causal Discovery
Yuxuan Wang, Mingzhou Liu, Xinwei Sun, Wei Wang, Yizhou Wang Bayesian Inference for Correlated Human Experts and Classifiers
Markelle Kelly, Alex James Boyd, Sam Showalter, Mark Steyvers, Padhraic Smyth Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks
Dongwoo Lee, Dong Bok Lee, Steven Adriaensen, Juho Lee, Sung Ju Hwang, Frank Hutter, Seon Joo Kim, Hae Beom Lee Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
Aya Kayal, Sattar Vakili, Laura Toni, Da-Shan Shiu, Alberto Bernacchia BCE vs. CE in Deep Feature Learning
Qiufu Li, Huibin Xiao, Linlin Shen Be Confident: Uncovering Overfitting in MLLM Multi-Task Tuning
Wenke Huang, Jian Liang, Guancheng Wan, Didi Zhu, He Li, Jiawei Shao, Mang Ye, Bo Du, Dacheng Tao BECAME: Bayesian Continual Learning with Adaptive Model Merging
Mei Li, Yuxiang Lu, Qinyan Dai, Suizhi Huang, Yue Ding, Hongtao Lu Benchmarking Quantum Reinforcement Learning
Nico Meyer, Christian Ufrecht, George Yammine, Georgios Kontes, Christopher Mutschler, Daniel Scherer Best of Both Worlds: Advantages of Hybrid Graph Sequence Models
Ali Behrouz, Ali Parviz, Mahdi Karami, Clayton Sanford, Bryan Perozzi, Vahab Mirrokni Best of Both Worlds: Regret Minimization Versus Minimax Play
Adrian Müller, Jon Schneider, Stratis Skoulakis, Luca Viano, Volkan Cevher BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute
Dujian Ding, Ankur Mallick, Shaokun Zhang, Chi Wang, Daniel Madrigal, Mirian Del Carmen Hipolito Garcia, Menglin Xia, Laks V. S. Lakshmanan, Qingyun Wu, Victor Rühle Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling
Shuqi Lu, Xiaohong Ji, Bohang Zhang, Lin Yao, Siyuan Liu, Zhifeng Gao, Linfeng Zhang, Guolin Ke Beyond Matryoshka: Revisiting Sparse Coding for Adaptive Representation
Tiansheng Wen, Yifei Wang, Zequn Zeng, Zhong Peng, Yudi Su, Xinyang Liu, Bo Chen, Hongwei Liu, Stefanie Jegelka, Chenyu You Beyond Message Passing: Neural Graph Pattern Machine
Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions
Eray Erturk, Fahad Kamran, Salar Abbaspourazad, Sean Jewell, Harsh Sharma, Yujie Li, Sinead Williamson, Nicholas J Foti, Joseph Futoma BiAssemble: Learning Collaborative Affordance for Bimanual Geometric Assembly
Yan Shen, Ruihai Wu, Yubin Ke, Xinyuan Song, Zeyi Li, Xiaoqi Li, Hongwei Fan, Haoran Lu, Hao Dong BILBO: BILevel Bayesian Optimization
Ruth Wan Theng Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching Models
Susan Liang, Dejan Markovic, Israel D. Gebru, Steven Krenn, Todd Keebler, Jacob Sandakly, Frank Yu, Samuel Hassel, Chenliang Xu, Alexander Richard Bipartite Ranking from Multiple Labels: On Loss Versus Label Aggregation
Michal Lukasik, Lin Chen, Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Felix X. Yu, Sashank J. Reddi, Gang Fu, Mohammadhossein Bateni, Sanjiv Kumar Black-Box Adversarial Attacks on LLM-Based Code Completion
Slobodan Jenko, Niels Mündler, Jingxuan He, Mark Vero, Martin Vechev BoA: Attention-Aware Post-Training Quantization Without Backpropagation
Junhan Kim, Ho-Young Kim, Eulrang Cho, Chungman Lee, Joonyoung Kim, Yongkweon Jeon Bongard in Wonderland: Visual Puzzles That Still Make AI Go Mad?
Antonia Wüst, Tim Tobiasch, Lukas Helff, Inga Ibs, Wolfgang Stammer, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting BOOD: Boundary-Based Out-of-Distribution Data Generation
Qilin Liao, Shuo Yang, Bo Zhao, Ping Luo, Hengshuang Zhao Boosting Virtual Agent Learning and Reasoning: A Step-Wise, Multi-Dimensional, and Generalist Reward Model with Benchmark
Bingchen Miao, Yang Wu, Minghe Gao, Qifan Yu, Wendong Bu, Wenqiao Zhang, Yunfei Li, Siliang Tang, Tat-Seng Chua, Juncheng Li Bounded Rationality for LLMs: Satisficing Alignment at Inference-Time
Mohamad Fares El Hajj Chehade, Soumya Suvra Ghosal, Souradip Chakraborty, Avinash Reddy, Dinesh Manocha, Hao Zhu, Amrit Singh Bedi Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
Zhining Liu, Ze Yang, Xiao Lin, Ruizhong Qiu, Tianxin Wei, Yada Zhu, Hendrik Hamann, Jingrui He, Hanghang Tong Bridging Layout and RTL: Knowledge Distillation Based Timing Prediction
Mingjun Wang, Yihan Wen, Bin Sun, Jianan Mu, Juan Li, Xiaoyi Wang, Jing Justin Ye, Bei Yu, Huawei Li Bring Reason to Vision: Understanding Perception and Reasoning Through Model Merging
Shiqi Chen, Jinghan Zhang, Tongyao Zhu, Wei Liu, Siyang Gao, Miao Xiong, Manling Li, Junxian He BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning
Han Zhong, Yutong Yin, Shenao Zhang, Xiaojun Xu, Yuanxin Liu, Yifei Zuo, Zhihan Liu, Boyi Liu, Sirui Zheng, Hongyi Guo, Liwei Wang, Mingyi Hong, Zhaoran Wang Broadband Ground Motion Synthesis by Diffusion Model with Minimal Condition
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Yu Liang, Yu Yang, Wenjie Wei, Ammar Belatreche, Shuai Wang, Malu Zhang, Yang Yang CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging
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Jiayuan Zhang, Xuefeng Liu, Jianwei Niu, Shaojie Tang, Haotian Yang, Xinghao Wu Cavia: Camera-Controllable Multi-View Video Diffusion with View-Integrated Attention
Dejia Xu, Yifan Jiang, Chen Huang, Liangchen Song, Thorsten Gernoth, Liangliang Cao, Zhangyang Wang, Hao Tang CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and Acquisition
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Matthew Robert Wicker, Philip Sosnin, Igor Shilov, Adrianna Janik, Mark Niklas Mueller, Yves-Alexandre De Montjoye, Adrian Weller, Calvin Tsay Certified Unlearning for Neural Networks
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Yi He, Yiming Yang, Xiaoyuan Cheng, Hai Wang, Xiao Xue, Boli Chen, Yukun Hu Chip Placement with Diffusion Models
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Fanxu Meng, Pingzhi Tang, Fan Jiang, Muhan Zhang Clustering Properties of Self-Supervised Learning
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Tianze Yang, Yucheng Shi, Mengnan Du, Xuansheng Wu, Qiaoyu Tan, Jin Sun, Ninghao Liu ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
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Fei Zhang, Pei Zhang, Baosong Yang, Fei Huang, Yanfeng Wang, Ya Zhang Contextual Bandits for Unbounded Context Distributions
Puning Zhao, Rongfei Fan, Shaowei Wang, Li Shen, Qixin Zhang, Zong Ke, Tianhang Zheng Contextures: Representations from Contexts
Runtian Zhai, Kai Yang, Burak Varıcı, Che-Ping Tsai, J Zico Kolter, Pradeep Kumar Ravikumar Continuous Bayesian Model Selection for Multivariate Causal Discovery
Anish Dhir, Ruby Sedgwick, Avinash Kori, Ben Glocker, Mark Van Der Wilk Continuous Semi-Implicit Models
Longlin Yu, Jiajun Zha, Tong Yang, Tianyu Xie, Xiangyu Zhang, S.-H. Chan, Cheng Zhang Continuous-Time Analysis of Heavy Ball Momentum in Min-Max Games
Yi Feng, Kaito Fujii, Stratis Skoulakis, Xiao Wang, Volkan Cevher Contour Integration Underlies Human-like Vision
Ben Lonnqvist, Elsa Scialom, Abdulkadir Gokce, Zehra Merchant, Michael Herzog, Martin Schrimpf Contract Design Under Approximate Best Responses
Francesco Bacchiocchi, Jiarui Gan, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti Contrastive Localized Language-Image Pre-Training
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Ian Gemp, Andreas Alexander Haupt, Luke Marris, Siqi Liu, Georgios Piliouras Copilot Arena: A Platform for Code LLM Evaluation in the Wild
Wayne Chi, Valerie Chen, Anastasios Nikolas Angelopoulos, Wei-Lin Chiang, Aditya Mittal, Naman Jain, Tianjun Zhang, Ion Stoica, Chris Donahue, Ameet Talwalkar CoPINN: Cognitive Physics-Informed Neural Networks
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Yaofo Chen, Zeng You, Shuhai Zhang, Haokun Li, Yirui Li, Yaowei Wang, Mingkui Tan Core Knowledge Deficits in Multi-Modal Language Models
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Elliot Myunghoon Kim, Avi Garg, Kenny Peng, Nikhil Garg Correlation Clustering Beyond the Pivot Algorithm
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Wenxu Wang, Rui Zhou, Jing Wang, Yun Zhou, Cheng Zhu, Ruichun Tang, Bo Han, Nevin L. Zhang CoSER: Coordinating LLM-Based Persona Simulation of Established Roles
Xintao Wang, Heng Wang, Yifei Zhang, Xinfeng Yuan, Rui Xu, Jen-Tse Huang, Siyu Yuan, Haoran Guo, Jiangjie Chen, Shuchang Zhou, Wei Wang, Yanghua Xiao Cost-Efficient Collaboration Between On-Device and Cloud Language Models
Avanika Narayan, Dan Biderman, Sabri Eyuboglu, Avner May, Scott Linderman, James Zou, Christopher Re CostFilter-AD: Enhancing Anomaly Detection Through Matching Cost Filtering
Zhe Zhang, Mingxiu Cai, Hanxiao Wang, Gaochang Wu, Tianyou Chai, Xiatian Zhu Covered Forest: Fine-Grained Generalization Analysis of Graph Neural Networks
Antonis Vasileiou, Ben Finkelshtein, Floris Geerts, Ron Levie, Christopher Morris Cowpox: Towards the Immunity of VLM-Based Multi-Agent Systems
Yutong Wu, Jie Zhang, Yiming Li, Chao Zhang, Qing Guo, Han Qiu, Nils Lukas, Tianwei Zhang Cradle: Empowering Foundation Agents Towards General Computer Control
Weihao Tan, Wentao Zhang, Xinrun Xu, Haochong Xia, Ziluo Ding, Boyu Li, Bohan Zhou, Junpeng Yue, Jiechuan Jiang, Yewen Li, Ruyi An, Molei Qin, Chuqiao Zong, Longtao Zheng, Yujie Wu, Xiaoqiang Chai, Yifei Bi, Tianbao Xie, Pengjie Gu, Xiyun Li, Ceyao Zhang, Long Tian, Chaojie Wang, Xinrun Wang, Börje F. Karlsson, Bo An, Shuicheng Yan, Zongqing Lu CRANE: Reasoning with Constrained LLM Generation
Debangshu Banerjee, Tarun Suresh, Shubham Ugare, Sasa Misailovic, Gagandeep Singh Critical Tokens Matter: Token-Level Contrastive Estimation Enhances LLM’s Reasoning Capability
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Meng Chen, Hongwei Jia, Zechen Li, Wenzhen Jia, Kai Zhao, Hongjun Dai, Weiming Huang Cross-Environment Cooperation Enables Zero-Shot Multi-Agent Coordination
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Feng Wu, Tsai Hor Chan, Fuying Wang, Guosheng Yin, Lequan Yu CSTrack: Enhancing RGB-X Tracking via Compact Spatiotemporal Features
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Shuhai Zhang, Zeng You, Yaofo Chen, Zhiquan Wen, Qianyue Wang, Zhijie Qiu, Yuanqing Li, Mingkui Tan Customizing the Inductive Biases of SoftMax Attention Using Structured Matrices
Yilun Kuang, Noah Amsel, Sanae Lotfi, Shikai Qiu, Andres Potapczynski, Andrew Gordon Wilson CVE-Bench: A Benchmark for AI Agents’ Ability to Exploit Real-World Web Application Vulnerabilities
Yuxuan Zhu, Antony Kellermann, Dylan Bowman, Philip Li, Akul Gupta, Adarsh Danda, Richard Fang, Conner Jensen, Eric Ihli, Jason Benn, Jet Geronimo, Avi Dhir, Sudhit Rao, Kaicheng Yu, Twm Stone, Daniel Kang DAMA: Data- and Model-Aware Alignment of Multi-Modal LLMs
Jinda Lu, Junkang Wu, Jinghan Li, Xiaojun Jia, Shuo Wang, Yifan Zhang, Junfeng Fang, Xiang Wang, Xiangnan He DataDecide: How to Predict Best Pretraining Data with Small Experiments
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Gen Li, Yao Wan, Hongyu Zhang, Zhou Zhao, Wenbin Jiang, Xuanhua Shi, Hai Jin, Zheng Wang DCBM: Data-Efficient Visual Concept Bottleneck Models
Katharina Prasse, Patrick Knab, Sascha Marton, Christian Bartelt, Margret Keuper DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space
Mang Ning, Mingxiao Li, Jianlin Su, Jia Haozhe, Lanmiao Liu, Martin Benes, Wenshuo Chen, Albert Ali Salah, Itir Onal Ertugrul DEALing with Image Reconstruction: Deep Attentive Least Squares
Mehrsa Pourya, Erich Kobler, Michael Unser, Sebastian Neumayer Decomposition of Graphic Design with Unified Multimodal Model
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Siyuan Duan, Yuan Sun, Dezhong Peng, Guiduo Duan, Xi Peng, Peng Hu Deep Neural Cellular Potts Models
Koen Minartz, Tim D’Hondt, Leon Hillmann, Jörn Starruß, Lutz Brusch, Vlado Menkovski Deep Streaming View Clustering
Honglin Yuan, Xingfeng Li, Jian Dai, Xiaojian You, Yuan Sun, Zhenwen Ren Deep Unsupervised Hashing via External Guidance
Qihong Song, Xiting Liu, Hongyuan Zhu, Joey Tianyi Zhou, Xi Peng, Peng Hu DeepCrossAttention: Supercharging Transformer Residual Connections
Mike Heddes, Adel Javanmard, Kyriakos Axiotis, Gang Fu, Mohammadhossein Bateni, Vahab Mirrokni DeepLayout: Learning Neural Representations of Circuit Placement Layout
Yuxiang Zhao, Zhuomin Chai, Xun Jiang, Qiang Xu, Runsheng Wang, Yibo Lin Defending LVLMs Against Vision Attacks Through Partial-Perception Supervision
Qi Zhou, Dongxia Wang, Tianlin Li, Yun Lin, Yang Liu, Jin Song Dong, Qing Guo DeFoG: Discrete Flow Matching for Graph Generation
Yiming Qin, Manuel Madeira, Dorina Thanou, Pascal Frossard Delta Decompression for MoE-Based LLMs Compression
Hao Gu, Wei Li, Lujun Li, Zhu Qiyuan, Mark G. Lee, Shengjie Sun, Wei Xue, Yike Guo Demeaned Sparse: Efficient Anomaly Detection by Residual Estimate
Yifan Fang, Yifei Fang, Ruizhe Chen, Haote Xu, Xinghao Ding, Yue Huang Demystifying Catastrophic Forgetting in Two-Stage Incremental Object Detector
Qirui Wu, Shizhou Zhang, De Cheng, Yinghui Xing, Di Xu, Peng Wang, Yanning Zhang Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
Youhe Jiang, Fangcheng Fu, Xiaozhe Yao, Guoliang He, Xupeng Miao, Ana Klimovic, Bin Cui, Binhang Yuan, Eiko Yoneki Demystifying Long Chain-of-Thought Reasoning
Shiming Yang, Yuxuan Tong, Xinyao Niu, Graham Neubig, Xiang Yue Dendritic Localized Learning: Toward Biologically Plausible Algorithm
Changze Lv, Jingwen Xu, Yiyang Lu, Xiaohua Wang, Zhenghua Wang, Zhibo Xu, Di Yu, Xin Du, Xiaoqing Zheng, Xuanjing Huang Density Ratio Estimation with Conditional Probability Paths
Hanlin Yu, Arto Klami, Aapo Hyvarinen, Anna Korba, Omar Chehab Dequantified Diffusion-Schrödinger Bridge for Density Ratio Estimation
Wei Chen, Shigui Li, Jiacheng Li, Junmei Yang, John Paisley, Delu Zeng Design Considerations in Offline Preference-Based RL
Alekh Agarwal, Christoph Dann, Teodor Vanislavov Marinov Designing Cyclic Peptides via Harmonic SDE with Atom-Bond Modeling
Xiangxin Zhou, Mingyu Li, Yi Xiao, Jiahan Li, Dongyu Xue, Zaixiang Zheng, Jianzhu Ma, Quanquan Gu Detecting Strategic Deception with Linear Probes
Nicholas Goldowsky-Dill, Bilal Chughtai, Stefan Heimersheim, Marius Hobbhahn Determinant Estimation Under Memory Constraints and Neural Scaling Laws
Siavash Ameli, Chris Van Der Heide, Liam Hodgkinson, Fred Roosta, Michael W. Mahoney DexScale: Automating Data Scaling for Sim2Real Generalizable Robot Control
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Ismail Alkhouri, Cedric Le Denmat, Yingjie Li, Cunxi Yu, Jia Liu, Rongrong Wang, Alvaro Velasquez Differentiable Solver Search for Fast Diffusion Sampling
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Taiyu Ban, Changxin Rong, Xiangyu Wang, Lyuzhou Chen, Xin Wang, Derui Lyu, Qinrui Zhu, Huanhuan Chen Differential Coding for Training-Free ANN-to-SNN Conversion
Zihan Huang, Wei Fang, Tong Bu, Peng Xue, Zecheng Hao, Wenxuan Liu, Yuanhong Tang, Zhaofei Yu, Tiejun Huang Differential Privacy Guarantees of Markov Chain Monte Carlo Algorithms
Andrea Bertazzi, Tim Johnston, Gareth O. Roberts, Alain Oliviero Durmus Differential Privacy Under Class Imbalance: Methods and Empirical Insights
Lucas Rosenblatt, Yuliia Lut, Ethan Turok, Marco Avella Medina, Rachel Cummings Differentially Private Boxplots
Kelly Ramsay, Jairo Diaz-Rodriguez DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra
Montgomery Bohde, Mrunali Manjrekar, Runzhong Wang, Shuiwang Ji, Connor W. Coley Diffusion Adversarial Post-Training for One-Step Video Generation
Shanchuan Lin, Xin Xia, Yuxi Ren, Ceyuan Yang, Xuefeng Xiao, Lu Jiang Diffusion Counterfactual Generation with Semantic Abduction
Rajat R Rasal, Avinash Kori, Fabio De Sousa Ribeiro, Tian Xia, Ben Glocker Diffusion Instruction Tuning
Chen Jin, Ryutaro Tanno, Amrutha Saseendran, Tom Diethe, Philip Alexander Teare Diffusion on Language Model Encodings for Protein Sequence Generation
Viacheslav Meshchaninov, Pavel Strashnov, Andrey Shevtsov, Fedor Nikolaev, Nikita Ivanisenko, Olga Kardymon, Dmitry Vetrov Diffusion Sampling Correction via Approximately 10 Parameters
Guangyi Wang, Wei Peng, Lijiang Li, Wenyu Chen, Yuren Cai, Song-Zhi Su DiffusionVLA: Scaling Robot Foundation Models via Unified Diffusion and Autoregression
Junjie Wen, Yichen Zhu, Minjie Zhu, Zhibin Tang, Jinming Li, Zhongyi Zhou, Xiaoyu Liu, Chaomin Shen, Yaxin Peng, Feifei Feng DiMa: Understanding the Hardness of Online Matching Problems via Diffusion Models
Boyu Zhang, Aocheng Shen, Bing Liu, Qiankun Zhang, Bin Yuan, Jing Wang, Shenghao Liu, Xianjun Deng DIME: Diffusion-Based Maximum Entropy Reinforcement Learning
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Sifan Yang, Yuanyu Wan, Peijia Li, Yibo Wang, Xiao Zhang, Zhewei Wei, Lijun Zhang DipLLM: Fine-Tuning LLM for Strategic Decision-Making in Diplomacy
Kaixuan Xu, Jiajun Chai, Sicheng Li, Yuqian Fu, Yuanheng Zhu, Dongbin Zhao Direct Motion Models for Assessing Generated Videos
Kelsey R Allen, Carl Doersch, Guangyao Zhou, Mohammed Suhail, Danny Driess, Ignacio Rocco, Yulia Rubanova, Thomas Kipf, Mehdi S. M. Sajjadi, Kevin Patrick Murphy, Joao Carreira, Sjoerd Van Steenkiste Direct Prediction Set Minimization via Bilevel Conformal Classifier Training
Yuanjie Shi, Hooman Shahrokhi, Xuesong Jia, Xiongzhi Chen, Jana Doppa, Yan Yan Directed Graph Grammars for Sequence-Based Learning
Michael Sun, Orion Foo, Gang Liu, Wojciech Matusik, Jie Chen Directly Forecasting Belief for Reinforcement Learning with Delays
Qingyuan Wu, Yuhui Wang, Simon Sinong Zhan, Yixuan Wang, Chung-Wei Lin, Chen Lv, Qi Zhu, Jürgen Schmidhuber, Chao Huang Discovering Latent Causal Graphs from Spatiotemporal Data
Kun Wang, Sumanth Varambally, Duncan Watson-Parris, Yian Ma, Rose Yu Discovering Spoofing Attempts on Language Model Watermarks
Thibaud Gloaguen, Nikola Jovanović, Robin Staab, Martin Vechev Discovering Symbolic Cognitive Models from Human and Animal Behavior
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Gleb Rodionov, Liudmila Prokhorenkova Discriminative Finetuning of Generative Large Language Models Without Reward Models and Human Preference Data
Siqi Guo, Ilgee Hong, Vicente Balmaseda, Changlong Yu, Liang Qiu, Xin Liu, Haoming Jiang, Tuo Zhao, Tianbao Yang Discriminative Policy Optimization for Token-Level Reward Models
Hongzhan Chen, Tao Yang, Shiping Gao, Ruijun Chen, Xiaojun Quan, Hongtao Tian, Ting Yao Disentangled Graph Spectral Domain Adaptation
Liang Yang, Xin Chen, Jiaming Zhuo, Di Jin, Chuan Wang, Xiaochun Cao, Zhen Wang, Yuanfang Guo Distillation of Discrete Diffusion Through Dimensional Correlations
Satoshi Hayakawa, Yuhta Takida, Masaaki Imaizumi, Hiromi Wakaki, Yuki Mitsufuji Distillation Scaling Laws
Dan Busbridge, Amitis Shidani, Floris Weers, Jason Ramapuram, Etai Littwin, Russell Webb Distilling the Knowledge in Data Pruning
Emanuel Ben Baruch, Adam Botach, Igor Kviatkovsky, Manoj Aggarwal, Gerard Medioni DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs
Jongwoo Ko, Tianyi Chen, Sungnyun Kim, Tianyu Ding, Luming Liang, Ilya Zharkov, Se-Young Yun Distributed Differentially Private Data Analytics via Secure Sketching
Jakob Burkhardt, Hannah Keller, Claudio Orlandi, Chris Schwiegelshohn Distributed Event-Based Learning via ADMM
Guner Dilsad Er, Sebastian Trimpe, Michael Muehlebach Distribution-Aware Fairness Learning in Medical Image Segmentation from a Control-Theoretic Perspective
Yujin Oh, Pengfei Jin, Sangjoon Park, Sekeun Kim, Siyeop Yoon, Jin Sung Kim, Kyungsang Kim, Xiang Li, Quanzheng Li Distributional Diffusion Models with Scoring Rules
Valentin De Bortoli, Alexandre Galashov, J Swaroop Guntupalli, Guangyao Zhou, Kevin Patrick Murphy, Arthur Gretton, Arnaud Doucet Distributionally Robust Active Learning for Gaussian Process Regression
Shion Takeno, Yoshito Okura, Yu Inatsu, Aoyama Tatsuya, Tomonari Tanaka, Akahane Satoshi, Hiroyuki Hanada, Noriaki Hashimoto, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation
Dongya Jia, Zhuo Chen, Jiawei Chen, Chenpeng Du, Jian Wu, Jian Cong, Xiaobin Zhuang, Chumin Li, Zhen Wei, Yuping Wang, Yuxuan Wang Diverging Preferences: When Do Annotators Disagree and Do Models Know?
Michael Jq Zhang, Zhilin Wang, Jena D. Hwang, Yi Dong, Olivier Delalleau, Yejin Choi, Eunsol Choi, Xiang Ren, Valentina Pyatkin Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift
Nguyen Nhat Minh To, Paul F R Wilson, Viet Nguyen, Mohamed Harmanani, Michael Cooper, Fahimeh Fooladgar, Purang Abolmaesumi, Parvin Mousavi, Rahul Krishnan Diversifying Policy Behaviors with Extrinsic Behavioral Curiosity
Zhenglin Wan, Xingrui Yu, David Mark Bossens, Yueming Lyu, Qing Guo, Flint Xiaofeng Fan, Yew-Soon Ong, Ivor Tsang Divide and Conquer: Exploring Language-Centric Tree Reasoning for Video Question-Answering
Zhaohe Liao, Jiangtong Li, Siyu Sun, Qingyang Liu, Fengshun Xiao, Tianjiao Li, Qiang Zhang, Guang Chen, Li Niu, Changjun Jiang, Liqing Zhang Diving into Self-Evolving Training for Multimodal Reasoning
Wei Liu, Junlong Li, Xiwen Zhang, Fan Zhou, Yu Cheng, Junxian He DLP: Dynamic Layerwise Pruning in Large Language Models
Yuli Chen, Bo Cheng, Jiale Han, Yingying Zhang, Yingting Li, Shuhao Zhang Do Multiple Instance Learning Models Transfer?
Daniel Shao, Richard J. Chen, Andrew H. Song, Joel Runevic, Ming Y. Lu, Tong Ding, Faisal Mahmood Do NOT Think That Much for 2+3=? on the Overthinking of Long Reasoning Models
Xingyu Chen, Jiahao Xu, Tian Liang, Zhiwei He, Jianhui Pang, Dian Yu, Linfeng Song, Qiuzhi Liu, Mengfei Zhou, Zhuosheng Zhang, Rui Wang, Zhaopeng Tu, Haitao Mi, Dong Yu Do We Really Need Message Passing in Brain Network Modeling?
Liang Yang, Yuwei Liu, Jiaming Zhuo, Di Jin, Chuan Wang, Zhen Wang, Xiaochun Cao DocVXQA: Context-Aware Visual Explanations for Document Question Answering
Mohamed Ali Souibgui, Changkyu Choi, Andrey Barsky, Kangsoo Jung, Ernest Valveny, Dimosthenis Karatzas Does Learning the Right Latent Variables Necessarily Improve In-Context Learning?
Sarthak Mittal, Eric Elmoznino, Leo Gagnon, Sangnie Bhardwaj, Guillaume Lajoie, Dhanya Sridhar DOLPHIN: A Programmable Framework for Scalable Neurosymbolic Learning
Aaditya Naik, Jason Liu, Claire Wang, Amish Sethi, Saikat Dutta, Mayur Naik, Eric Wong Don’t Restart, Just Reuse: Reoptimizing MILPs with Dynamic Parameters
Sijia Zhang, Shuli Zeng, Shaoang Li, Feng Wu, Shaojie Tang, Xiangyang Li DPO Meets PPO: Reinforced Token Optimization for RLHF
Han Zhong, Zikang Shan, Guhao Feng, Wei Xiong, Xinle Cheng, Li Zhao, Di He, Jiang Bian, Liwei Wang DriveGPT: Scaling Autoregressive Behavior Models for Driving
Xin Huang, Eric M Wolff, Paul Vernaza, Tung Phan-Minh, Hongge Chen, David S Hayden, Mark Edmonds, Brian Pierce, Xinxin Chen, Pratik Elias Jacob, Xiaobai Chen, Chingiz Tairbekov, Pratik Agarwal, Tianshi Gao, Yuning Chai, Siddhartha Srinivasa DS-VLM: Diffusion Supervision Vision Language Model
Zhen Sun, Yunhang Shen, Jie Li, Xing Sun, Pingyang Dai, Liujuan Cao, Rongrong Ji DSP: Dynamic Sequence Parallelism for Multi-Dimensional Transformers
Xuanlei Zhao, Shenggan Cheng, Chang Chen, Zangwei Zheng, Ziming Liu, Zheming Yang, Yang You DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications
Ibrahim Fayad, Max Zimmer, Martin Schwartz, Fabian Gieseke, Philippe Ciais, Gabriel Belouze, Sarah Brood, Aurélien De Truchis, Alexandre D’Aspremont DVI:A Derivative-Based Vision Network for INR
Runzhao Yang, Xiaolong Wu, Zhihong Zhang, Fabian Zhang, Tingxiong Xiao, Zongren Li, Kunlun He, Jinli Suo Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning
Chendi Ge, Xin Wang, Zeyang Zhang, Hong Chen, Jiapei Fan, Longtao Huang, Hui Xue, Wenwu Zhu Dynamic Sparse Training of Diagonally Sparse Networks
Abhishek Tyagi, Arjun Iyer, William H Renninger, Christopher Kanan, Yuhao Zhu Dynamical Phases of Short-Term Memory Mechanisms in RNNs
Bariscan Kurtkaya, Fatih Dinc, Mert Yuksekgonul, Marta Blanco-Pozo, Ege Cirakman, Mark Schnitzer, Yucel Yemez, Hidenori Tanaka, Peng Yuan, Nina Miolane DynaMind: Reasoning over Abstract Video Dynamics for Embodied Decision-Making
Ziru Wang, Mengmeng Wang, Jade Dai, Teli Ma, Guo-Jun Qi, Yong Liu, Guang Dai, Jingdong Wang EARTH: Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph
Guancheng Wan, Zewen Liu, Xiaojun Shan, Max Sy Lau, B. Aditya Prakash, Wei Jin EasyInv: Toward Fast and Better DDIM Inversion
Ziyue Zhang, Mingbao Lin, Shuicheng Yan, Rongrong Ji EasyRef: Omni-Generalized Group Image Reference for Diffusion Models via Multimodal LLM
Zhuofan Zong, Dongzhi Jiang, Bingqi Ma, Guanglu Song, Hao Shao, Dazhong Shen, Yu Liu, Hongsheng Li EcoMapper: Generative Modeling for Climate-Aware Satellite Imagery
Muhammed Goktepe, Amir Hossein Shamseddin, Erencan Uysal, Javier Muinelo Monteagudo, Lukas Drees, Aysim Toker, Senthold Asseng, Malte Von Bloh Editable Concept Bottleneck Models
Lijie Hu, Chenyang Ren, Zhengyu Hu, Hongbin Lin, Cheng-Long Wang, Zhen Tan, Weimin Lyu, Jingfeng Zhang, Hui Xiong, Di Wang EditLord: Learning Code Transformation Rules for Code Editing
Weichen Li, Albert Jan, Baishakhi Ray, Junfeng Yang, Chengzhi Mao, Kexin Pei Effective and Efficient Masked Image Generation Models
Zebin You, Jingyang Ou, Xiaolu Zhang, Jun Hu, Jun Zhou, Chongxuan Li Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs
Xun Wang, Jing Xu, Franziska Boenisch, Michael Backes, Christopher A. Choquette-Choo, Adam Dziedzic Efficient and Scalable Density Functional Theory Hamiltonian Prediction Through Adaptive Sparsity
Erpai Luo, Xinran Wei, Lin Huang, Yunyang Li, Han Yang, Zaishuo Xia, Zun Wang, Chang Liu, Bin Shao, Jia Zhang Efficient ANN-SNN Conversion with Error Compensation Learning
Chang Liu, Jiangrong Shen, Xuming Ran, Mingkun Xu, Qi Xu, Yi Xu, Gang Pan Efficient Federated Incomplete Multi-View Clustering
Suyuan Liu, Hao Yu, Hao Tan, Ke Liang, Siwei Wang, Shengju Yu, En Zhu, Xinwang Liu Efficient Heterogeneity-Aware Federated Active Data Selection
Ying-Peng Tang, Chao Ren, Xiaoli Tang, Sheng-Jun Huang, Lizhen Cui, Han Yu Efficient Long Context Fine-Tuning with Chunk Flow
Xiulong Yuan, Hongtao Xu, Wenting Shen, Ang Wang, Xiafei Qiu, Jie Zhang, Yuqiong Liu, Bowen Yu, Junyang Lin, Mingzhen Li, Weile Jia, Yong Li, Wei Lin Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow
Zhonglin Cao, Mario Geiger, Allan Dos Santos Costa, Danny Reidenbach, Karsten Kreis, Tomas Geffner, Franco Pellegrini, Guoqing Zhou, Emine Kucukbenli Efficient Motion Prompt Learning for Robust Visual Tracking
Jie Zhao, Xin Chen, Yongsheng Yuan, Michael Felsberg, Dong Wang, Huchuan Lu Efficient Network Automatic Relevance Determination
Hongwei Zhang, Ziqi Ye, Xinyuan Wang, Xin Guo, Zenglin Xu, Yuan Cheng, Zixin Hu, Yuan Qi Efficient Noise Calculation in Deep Learning-Based MRI Reconstructions
Onat Dalmaz, Arjun D Desai, Reinhard Heckel, Tolga Cukur, Akshay S Chaudhari, Brian Hargreaves Efficient Robotic Policy Learning via Latent Space Backward Planning
Dongxiu Liu, Haoyi Niu, Zhihao Wang, Jinliang Zheng, Yinan Zheng, Zhonghong Ou, Jianming Hu, Jianxiong Li, Xianyuan Zhan Efficient Robust Conformal Prediction via Lipschitz-Bounded Networks
Thomas Massena, Léo Andéol, Thibaut Boissin, Franck Mamalet, Corentin Friedrich, Mathieu Serrurier, Sébastien Gerchinovitz Efficient Skill Discovery via Regret-Aware Optimization
He Zhang, Ming Zhou, Shaopeng Zhai, Ying Sun, Hui Xiong Efficiently Access Diffusion Fisher: Within the Outer Product Span Space
Fangyikang Wang, Hubery Yin, Shaobin Zhuang, Huminhao Zhu, Yinan Li, Lei Qian, Chao Zhang, Hanbin Zhao, Hui Qian, Chen Li Efficiently Serving Large Multimodal Models Using EPD Disaggregation
Gursimran Singh, Xinglu Wang, Yifan Hu, Timothy Tin Long Yu, Linzi Xing, Wei Jiang, Zhefeng Wang, Bai Xiaolong, Yi Li, Ying Xiong, Yong Zhang, Zhenan Fan Efficiently Vectorized MCMC on Modern Accelerators
Hugh Dance, Pierre Glaser, Peter Orbanz, Ryan P Adams EffiCoder: Enhancing Code Generation in Large Language Models Through Efficiency-Aware Fine-Tuning
Dong Huang, Guangtao Zeng, Jianbo Dai, Meng Luo, Han Weng, Yuhao Qing, Heming Cui, Zhijiang Guo, Jie Zhang EgoPrivacy: What Your First-Person Camera Says About You?
Yijiang Li, Genpei Zhang, Jiacheng Cheng, Yi Li, Xiaojun Shan, Dashan Gao, Jiancheng Lyu, Yuan Li, Ning Bi, Nuno Vasconcelos Ehrenfeucht-Haussler Rank and Chain of Thought
Pablo Barcelo, Alexander Kozachinskiy, Tomasz Steifer Eliciting Language Model Behaviors with Investigator Agents
Xiang Lisa Li, Neil Chowdhury, Daniel D. Johnson, Tatsunori Hashimoto, Percy Liang, Sarah Schwettmann, Jacob Steinhardt ELITE: Enhanced Language-Image Toxicity Evaluation for Safety
Wonjun Lee, Doehyeon Lee, Eugene Choi, Sangyoon Yu, Ashkan Yousefpour, Haon Park, Bumsub Ham, Suhyun Kim Elucidating the Design Space of Language Models for Image Generation
Xuantong Liu, Shaozhe Hao, Xianbiao Qi, Tianyang Hu, Jun Wang, Rong Xiao, Yuan Yao Elucidating the Design Space of Multimodal Protein Language Models
Cheng-Yen Hsieh, Xinyou Wang, Daiheng Zhang, Dongyu Xue, Fei Ye, Shujian Huang, Zaixiang Zheng, Quanquan Gu EmbodiedBench: Comprehensive Benchmarking Multi-Modal Large Language Models for Vision-Driven Embodied Agents
Rui Yang, Hanyang Chen, Junyu Zhang, Mark Zhao, Cheng Qian, Kangrui Wang, Qineng Wang, Teja Venkat Koripella, Marziyeh Movahedi, Manling Li, Heng Ji, Huan Zhang, Tong Zhang Emergence in Non-Neural Models: Grokking Modular Arithmetic via Average Gradient Outer Product
Neil Rohit Mallinar, Daniel Beaglehole, Libin Zhu, Adityanarayanan Radhakrishnan, Parthe Pandit, Mikhail Belkin Emergent Misalignment: Narrow Finetuning Can Produce Broadly Misaligned LLMs
Jan Betley, Daniel Chee Hian Tan, Niels Warncke, Anna Sztyber-Betley, Xuchan Bao, Martı́n Soto, Nathan Labenz, Owain Evans Emergent Response Planning in LLMs
Zhichen Dong, Zhanhui Zhou, Zhixuan Liu, Chao Yang, Chaochao Lu Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models
Yukang Yang, Declan Iain Campbell, Kaixuan Huang, Mengdi Wang, Jonathan D. Cohen, Taylor Whittington Webb EmoGrowth: Incremental Multi-Label Emotion Decoding with Augmented Emotional Relation Graph
Kaicheng Fu, Changde Du, Jie Peng, Kunpeng Wang, Shuangchen Zhao, Xiaoyu Chen, Huiguang He Emotional Face-to-Speech
Jiaxin Ye, Boyuan Cao, Hongming Shan Empirical Privacy Variance
Yuzheng Hu, Fan Wu, Ruicheng Xian, Yuhang Liu, Lydia Zakynthinou, Pritish Kamath, Chiyuan Zhang, David Forsyth Empower Structure-Based Molecule Optimization with Gradient Guided Bayesian Flow Networks
Keyue Qiu, Yuxuan Song, Jie Yu, Hongbo Ma, Ziyao Cao, Zhilong Zhang, Yushuai Wu, Mingyue Zheng, Hao Zhou, Wei-Ying Ma Empowering World Models with Reflection for Embodied Video Prediction
Xiaowei Chi, Chun-Kai Fan, Hengyuan Zhang, Xingqun Qi, Rongyu Zhang, Anthony Chen, Chi-Min Chan, Wei Xue, Qifeng Liu, Shanghang Zhang, Yike Guo ENAHPool: The Edge-Node Attention-Based Hierarchical Pooling for Graph Neural Networks
Zhehan Zhao, Lu Bai, Lixin Cui, Ming Li, Ziyu Lyu, Lixiang Xu, Yue Wang, Edwin Hancock End-to-End Learning Framework for Solving Non-Markovian Optimal Control
Xiaole Zhang, Peiyu Zhang, Xiongye Xiao, Shixuan Li, Vasileios Tzoumas, Vijay Gupta, Paul Bogdan Energy-Based Flow Matching for Generating 3D Molecular Structure
Wenyin Zhou, Christopher Iliffe Sprague, Vsevolod Viliuga, Matteo Tadiello, Arne Elofsson, Hossein Azizpour Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration
Andreas Kontogiannis, Konstantinos Papathanasiou, Yi Shen, Giorgos Stamou, Michael M. Zavlanos, George Vouros Enhancing Foundation Models for Time Series Forecasting via Wavelet-Based Tokenization
Luca Masserano, Abdul Fatir Ansari, Boran Han, Xiyuan Zhang, Christos Faloutsos, Michael W. Mahoney, Andrew Gordon Wilson, Youngsuk Park, Syama Sundar Rangapuram, Danielle C. Maddix, Bernie Wang Enhancing Foundation Models with Federated Domain Knowledge Infusion
Jiaqi Wang, Jingtao Li, Weiming Zhuang, Chen Chen, Lingjuan Lyu, Fenglong Ma Enhancing Graph Contrastive Learning for Protein Graphs from Perspective of Invariance
Yusong Wang, Shiyin Tan, Jialun Shen, Yicheng Xu, Haobo Song, Qi Xu, Prayag Tiwari, Mingkun Xu Enhancing Graph Invariant Learning from a Negative Inference Perspective
Kuo Yang, Zhengyang Zhou, Qihe Huang, Wenjie Du, Limin Li, Wu Jiang, Yang Wang Enhancing Target-Unspecific Tasks Through a Features Matrix
Fangming Cui, Yonggang Zhang, Xuan Wang, Xinmei Tian, Jun Yu Enhancing Visual Localization with Cross-Domain Image Generation
Yuanze Wang, Yichao Yan, Shiming Song, Songchang Jin, Yilan Huang, Xingdong Sheng, Dianxi Shi EnIGMA: Interactive Tools Substantially Assist LM Agents in Finding Security Vulnerabilities
Talor Abramovich, Meet Udeshi, Minghao Shao, Kilian Lieret, Haoran Xi, Kimberly Milner, Sofija Jancheska, John Yang, Carlos E Jimenez, Farshad Khorrami, Prashanth Krishnamurthy, Brendan Dolan-Gavitt, Muhammad Shafique, Karthik R Narasimhan, Ramesh Karri, Ofir Press Ensemble Distribution Distillation via Flow Matching
Jonggeon Park, Giung Nam, Hyunsu Kim, Jongmin Yoon, Juho Lee EPIC: Efficient Position-Independent Caching for Serving Large Language Models
Junhao Hu, Wenrui Huang, Weidong Wang, Haoyi Wang, Tiancheng Hu, Zhang Qin, Hao Feng, Xusheng Chen, Yizhou Shan, Tao Xie EpiCoder: Encompassing Diversity and Complexity in Code Generation
Yaoxiang Wang, Haoling Li, Xin Zhang, Jie Wu, Xiao Liu, Wenxiang Hu, Zhongxin Guo, Yangyu Huang, Ying Xin, Yujiu Yang, Jinsong Su, Qi Chen, Scarlett Li Epsilon-VAE: Denoising as Visual Decoding
Long Zhao, Sanghyun Woo, Ziyu Wan, Yandong Li, Han Zhang, Boqing Gong, Hartwig Adam, Xuhui Jia, Ting Liu Equivalence Is All: A Unified View for Self-Supervised Graph Learning
Yejiang Wang, Yuhai Zhao, Zhengkui Wang, Ling Li, Jiapu Wang, Fangting Li, Miaomiao Huang, Shirui Pan, Xingwei Wang Equivariant Neural Tangent Kernels
Philipp Misof, Pan Kessel, Jan E Gerken Equivariant Polynomial Functional Networks
Thieu Vo, Hoang V. Tran, Tho Tran Huu, An Nguyen The, Thanh Tran, Minh-Khoi Nguyen-Nhat, Duy-Tung Pham, Tan Minh Nguyen EraseAnything: Enabling Concept Erasure in Rectified Flow Transformers
Daiheng Gao, Shilin Lu, Wenbo Zhou, Jiaming Chu, Jie Zhang, Mengxi Jia, Bang Zhang, Zhaoxin Fan, Weiming Zhang Ergodic Generative Flows
Leo Maxime Brunswic, Mateo Clémente, Rui Heng Yang, Adam Sigal, Amir Rasouli, Yinchuan Li ESPFormer: Doubly-Stochastic Attention with Expected Sliced Transport Plans
Ashkan Shahbazi, Elaheh Akbari, Darian Salehi, Xinran Liu, Navid Naderializadeh, Soheil Kolouri ETTA: Elucidating the Design Space of Text-to-Audio Models
Sang-Gil Lee, Zhifeng Kong, Arushi Goel, Sungwon Kim, Rafael Valle, Bryan Catanzaro Evaluating LLMs Across Multi-Cognitive Levels: From Medical Knowledge Mastery to Scenario-Based Problem Solving
Yuxuan Zhou, Xien Liu, Chenwei Yan, Chen Ning, Xiao Zhang, Boxun Li, Xiangling Fu, Shijin Wang, Guoping Hu, Yu Wang, Ji Wu Event-Customized Image Generation
Zhen Wang, Yilei Jiang, Dong Zheng, Jun Xiao, Long Chen Everything Everywhere All at Once: LLMs Can In-Context Learn Multiple Tasks in Superposition
Zheyang Xiong, Ziyang Cai, John Cooper, Albert Ge, Vasilis Papageorgiou, Zack Sifakis, Angeliki Giannou, Ziqian Lin, Liu Yang, Saurabh Agarwal, Grigorios Chrysos, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos EvoControl: Multi-Frequency Bi-Level Control for High-Frequency Continuous Control
Samuel Holt, Todor Davchev, Dhruva Tirumala, Ben Moran, Atil Iscen, Antoine Laurens, Yixin Lin, Erik Frey, Markus Wulfmeier, Francesco Romano, Nicolas Heess EVOLvE: Evaluating and Optimizing LLMs for In-Context Exploration
Allen Nie, Yi Su, Bo Chang, Jonathan Lee, Ed H. Chi, Quoc V Le, Minmin Chen ExLM: Rethinking the Impact of $\texttt[MASK]$ Tokens in Masked Language Models
Kangjie Zheng, Junwei Yang, Siyue Liang, Bin Feng, Zequn Liu, Wei Ju, Zhiping Xiao, Ming Zhang Expected Variational Inequalities
Brian Hu Zhang, Ioannis Anagnostides, Emanuel Tewolde, Ratip Emin Berker, Gabriele Farina, Vincent Conitzer, Tuomas Sandholm Explaining the Role of Intrinsic Dimensionality in Adversarial Training
Enes Altinisik, Safa Messaoud, Husrev Taha Sencar, Hassan Sajjad, Sanjay Chawla Explaining, Fast and Slow: Abstraction and Refinement of Provable Explanations
Shahaf Bassan, Yizhak Yisrael Elboher, Tobias Ladner, Matthias Althoff, Guy Katz Explanatory Instructions: Towards Unified Vision Tasks Understanding and Zero-Shot Generalization
Yang Shen, Xiu-Shen Wei, Yifan Sun, Yuxin Song, Tao Yuan, Jian Jin, He-Yang Xu, Yazhou Yao, Errui Ding Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards
Yangsibo Huang, Milad Nasr, Anastasios Nikolas Angelopoulos, Nicholas Carlini, Wei-Lin Chiang, Christopher A. Choquette-Choo, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Ken Liu, Ion Stoica, Florian Tramèr, Chiyuan Zhang Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
Puning Yang, Qizhou Wang, Zhuo Huang, Tongliang Liu, Chengqi Zhang, Bo Han Exploring Invariance in Images Through One-Way Wave Equations
Yinpeng Chen, Dongdong Chen, Xiyang Dai, Mengchen Liu, Yinan Feng, Youzuo Lin, Lu Yuan, Zicheng Liu Exploring Large Action Sets with Hyperspherical Embeddings Using Von Mises-Fisher Sampling
Walid Bendada, Guillaume Salha-Galvan, Romain Hennequin, Théo Bontempelli, Thomas Bouabça, Tristan Cazenave Exploring Representations and Interventions in Time Series Foundation Models
Michał Wiliński, Mononito Goswami, Willa Potosnak, Nina Żukowska, Artur Dubrawski ExtPose: Robust and Coherent Pose Estimation by Extending ViTs
Rongyu Chen, Li’An Zhuo, Linlin Yang, Qi Wang, Liefeng Bo, Bang Zhang, Angela Yao Extracting Rare Dependence Patterns via Adaptive Sample Reweighting
Yiqing Li, Yewei Xia, Xiaofei Wang, Zhengming Chen, Liuhua Peng, Mingming Gong, Kun Zhang Extreme Value Policy Optimization for Safe Reinforcement Learning
Shiqing Gao, Yihang Zhou, Shuai Shao, Haoyu Luo, Yiheng Bing, Jiaxin Ding, Luoyi Fu, Xinbing Wang Fair Clustering via Alignment
Kunwoong Kim, Jihu Lee, Sangchul Park, Yongdai Kim Fairness on Principal Stratum: A New Perspective on Counterfactual Fairness
Haoxuan Li, Zeyu Tang, Zhichao Jiang, Zhuangyan Fang, Yue Liu, Zhi Geng, Kun Zhang FairPFN: A Tabular Foundation Model for Causal Fairness
Jake Robertson, Noah Hollmann, Samuel Müller, Noor Awad, Frank Hutter Falcon: Fast Visuomotor Policies via Partial Denoising
Haojun Chen, Minghao Liu, Chengdong Ma, Xiaojian Ma, Zailin Ma, Huimin Wu, Yuanpei Chen, Yifan Zhong, Mingzhi Wang, Qing Li, Yaodong Yang Fast and Low-Cost Genomic Foundation Models via Outlier Removal
Haozheng Luo, Chenghao Qiu, Maojiang Su, Zhihan Zhou, Zoe Mehta, Guo Ye, Jerry Yao-Chieh Hu, Han Liu Fast Estimation of Partial Dependence Functions Using Trees
Jinyang Liu, Tessa Steensgaard, Marvin N. Wright, Niklas Pfister, Munir Hiabu Fast Exact Unlearning for In-Context Learning Data for LLMs
Andrei Ioan Muresanu, Anvith Thudi, Michael R. Zhang, Nicolas Papernot Fast Inference with Kronecker-Sparse Matrices
Antoine Gonon, Léon Zheng, Pascal Carrivain, Tung Quoc Le Fast Large Language Model Collaborative Decoding via Speculation
Jiale Fu, Yuchu Jiang, Junkai Chen, Jiaming Fan, Xin Geng, Xu Yang Fast Min-$ε$ Segmented Regression Using Constant-Time Segment Merging
Ansgar Lößer, Max Schlecht, Florian Schintke, Joel Witzke, Matthias Weidlich, Björn Scheuermann Fast Tensor Completion via Approximate Richardson Iteration
Mehrdad Ghadiri, Matthew Fahrbach, Yunbum Kook, Ali Jadbabaie Fast Video Generation with Sliding Tile Attention
Peiyuan Zhang, Yongqi Chen, Runlong Su, Hangliang Ding, Ion Stoica, Zhengzhong Liu, Hao Zhang Fast, Accurate Manifold Denoising by Tunneling Riemannian Optimization
Shiyu Wang, Mariam Avagyan, Yihan Shen, Arnaud Lamy, Tingran Wang, Szabolcs Marka, Zsuzsanna Marka, John Wright Faster Approximation Algorithms for K-Center via Data Reduction
Arnold Filtser, Shaofeng H.-C. Jiang, Yi Li, Anurag Murty Naredla, Ioannis Psarros, Qiaoyuan Yang, Qin Zhang Faster Global Minimum Cut with Predictions
Helia Niaparast, Benjamin Moseley, Karan Singh FeatSharp: Your Vision Model Features, Sharper
Mike Ranzinger, Greg Heinrich, Pavlo Molchanov, Bryan Catanzaro, Andrew Tao Feature Importance Metrics in the Presence of Missing Data
Henrik Von Kleist, Joshua Wendland, Ilya Shpitser, Carsten Marr Feature Out! Let Raw Image as Your Condition for Blind Face Restoration
Xinmin Qiu, Chen Gege, Bonan Li, Congying Han, Tiande Guo, Zicheng Zhang Feature Shift Localization Network
Mı́riam Barrabés, Daniel Mas Montserrat, Kapal Dev, Alexander G. Ioannidis Federated In-Context Learning: Iterative Refinement for Improved Answer Quality
Ruhan Wang, Zhiyong Wang, Chengkai Huang, Rui Wang, Tong Yu, Lina Yao, John C.S. Lui, Dongruo Zhou Federated Node-Level Clustering Network with Cross-Subgraph Link Mending
Jingxin Liu, Renda Han, Wenxuan Tu, Haotian Wang, Junlong Wu, Jieren Cheng FedOne: Query-Efficient Federated Learning for Black-Box Discrete Prompt Learning
Ganyu Wang, Jinjie Fang, Maxwell Juncheng Yin, Bin Gu, Xi Chen, Boyu Wang, Yi Chang, Charles Ling FedSMU: Communication-Efficient and Generalization-Enhanced Federated Learning Through Symbolic Model Updates
Xinyi Lu, Hao Zhang, Chenglin Li, Weijia Lu, Zhifei Yang, Wenrui Dai, Xiaodong Zhang, Xiaofeng Ma, Can Zhang, Junni Zou, Hongkai Xiong Feedforward Few-Shot Species Range Estimation
Christian Lange, Max Hamilton, Elijah Cole, Alexander Shepard, Samuel Heinrich, Angela Zhu, Subhransu Maji, Grant Van Horn, Oisin Mac Aodha Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
Marta Skreta, Tara Akhound-Sadegh, Viktor Ohanesian, Roberto Bondesan, Alan Aspuru-Guzik, Arnaud Doucet, Rob Brekelmans, Alexander Tong, Kirill Neklyudov FG-CLIP: Fine-Grained Visual and Textual Alignment
Chunyu Xie, Bin Wang, Fanjing Kong, Jincheng Li, Dawei Liang, Gengshen Zhang, Dawei Leng, Yuhui Yin FIC-TSC: Learning Time Series Classification with Fisher Information Constraint
Xiwen Chen, Wenhui Zhu, Peijie Qiu, Hao Wang, Huayu Li, Zihan Li, Yalin Wang, Aristeidis Sotiras, Abolfazl Razi Field Matching: An Electrostatic Paradigm to Generate and Transfer Data
Alexander Kolesov, S. I. Manukhov, Vladimir Vladimirovich Palyulin, Alexander Korotin FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain
Rohan Deb, Kiran Koshy Thekumparampil, Kousha Kalantari, Gaurush Hiranandani, Shoham Sabach, Branislav Kveton FLAM: Frame-Wise Language-Audio Modeling
Yusong Wu, Christos Tsirigotis, Ke Chen, Cheng-Zhi Anna Huang, Aaron Courville, Oriol Nieto, Prem Seetharaman, Justin Salamon FlashTP: Fused, Sparsity-Aware Tensor Product for Machine Learning Interatomic Potentials
Seung Yul Lee, Hojoon Kim, Yutack Park, Dawoon Jeong, Seungwu Han, Yeonhong Park, Jae W. Lee Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
Tao Li, Zhengbao He, Yujun Li, Yasheng Wang, Lifeng Shang, Xiaolin Huang FlatQuant: Flatness Matters for LLM Quantization
Yuxuan Sun, Ruikang Liu, Haoli Bai, Han Bao, Kang Zhao, Yuening Li, Jiaxin Hu, Xianzhi Yu, Lu Hou, Chun Yuan, Xin Jiang, Wulong Liu, Jun Yao Fleet of Agents: Coordinated Problem Solving with Large Language Models
Lars Henning Klein, Nearchos Potamitis, Roland Aydin, Robert West, Caglar Gulcehre, Akhil Arora Flexibility-Conditioned Protein Structure Design with Flow Matching
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Zihan Zhou, Yang Zhou, Zijie Zhang, Lingjuan Lyu, Da Yan, Ruoming Jin, Dejing Dou FlexiReID: Adaptive Mixture of Expert for Multi-Modal Person Re-Identification
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Aidan Curtis, Eric Li, Michael Noseworthy, Nishad Gothoskar, Sachin Chitta, Hui Li, Leslie Pack Kaelbling, Nicole E Carey Flow-Field Inference from Neural Data Using Deep Recurrent Networks
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Abheek Ghosh, Tzeh Yuan Neoh, Nicholas Teh, Giannis Tyrovolas Free Process Rewards Without Process Labels
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Edward Milsom, Ben Anson, Laurence Aitchison Function-to-Style Guidance of LLMs for Code Translation
Longhui Zhang, Bin Wang, Jiahao Wang, Xiaofeng Zhao, Min Zhang, Hao Yang, Meishan Zhang, Yu Li, Jing Li, Jun Yu, Min Zhang Fusing Reward and Dueling Feedback in Stochastic Bandits
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Arturs Berzins, Andreas Radler, Eric Volkmann, Sebastian Sanokowski, Sepp Hochreiter, Johannes Brandstetter GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing
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Omri Ben Hemo, Alon Zolfi, Oryan Yehezkel, Omer Hofman, Roman Vainshtein, Hisashi Kojima, Yuval Elovici, Asaf Shabtai GRAM: A Generative Foundation Reward Model for Reward Generalization
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Alon Beck, Noam Itzhak Levi, Yohai Bar-Sinai Grokking Beyond the Euclidean Norm of Model Parameters
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Mingquan Feng, Weixin Liao, Yixin Huang, Yifan Fu, Qifu Zheng, Junchi Yan Hessian Geometry of Latent Space in Generative Models
Alexander Lobashev, Dmitry Guskov, Maria Larchenko, Mikhail Tamm Hgformer: Hyperbolic Graph Transformer for Collaborative Filtering
Xin Yang, Xingrun Li, Heng Chang, Yang Jinze, Xihong Yang, Shengyu Tao, Maiko Shigeno, Ningkang Chang, Junfeng Wang, Dawei Yin, Erxue Min Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models
Lucy Xiaoyang Shi, Brian Ichter, Michael Robert Equi, Liyiming Ke, Karl Pertsch, Quan Vuong, James Tanner, Anna Walling, Haohuan Wang, Niccolo Fusai, Adrian Li-Bell, Danny Driess, Lachy Groom, Sergey Levine, Chelsea Finn Hidden No More: Attacking and Defending Private Third-Party LLM Inference
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Haibo Zhao, Dian Wang, Yizhe Zhu, Xupeng Zhu, Owen Lewis Howell, Linfeng Zhao, Yaoyao Qian, Robin Walters, Robert Platt Hierarchical Graph Tokenization for Molecule-Language Alignment
Yongqiang Chen, Quanming Yao, Juzheng Zhang, James Cheng, Yatao Bian Hierarchical Masked Autoregressive Models with Low-Resolution Token Pivots
Guangting Zheng, Yehao Li, Yingwei Pan, Jiajun Deng, Ting Yao, Yanyong Zhang, Tao Mei Hierarchical Reinforcement Learning with Targeted Causal Interventions
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Kaixuan Zhang, Hu Wang, Minxian Li, Mingwu Ren, Mao Ye, Xiatian Zhu High-Fidelity Simultaneous Speech-to-Speech Translation
Tom Labiausse, Laurent Mazaré, Edouard Grave, Alexandre Défossez, Neil Zeghidour Highly Compressed Tokenizer Can Generate Without Training
Lukas Lao Beyer, Tianhong Li, Xinlei Chen, Sertac Karaman, Kaiming He HiRemate: Hierarchical Approach for Efficient Re-Materialization of Neural Networks
Julia Gusak, Xunyi Zhao, Théotime Le Hellard, Zhe Li, Lionel Eyraud-Dubois, Olivier Beaumont History-Guided Video Diffusion
Kiwhan Song, Boyuan Chen, Max Simchowitz, Yilun Du, Russ Tedrake, Vincent Sitzmann Homophily Enhanced Graph Domain Adaptation
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Xingyue Huang, Pablo Barcelo, Michael M. Bronstein, Ismail Ilkan Ceylan, Mikhail Galkin, Juan L Reutter, Miguel Romero Orth How Far Is Video Generation from World Model: A Physical Law Perspective
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Sebastian Bordt, Suraj Srinivas, Valentyn Boreiko, Ulrike Von Luxburg How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects
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Xuekai Zhu, Daixuan Cheng, Hengli Li, Kaiyan Zhang, Ermo Hua, Xingtai Lv, Ning Ding, Zhouhan Lin, Zilong Zheng, Bowen Zhou How to Train Your Multi-Exit Model? Analyzing the Impact of Training Strategies
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Jue Gong, Jingkai Wang, Zheng Chen, Xing Liu, Hong Gu, Yulun Zhang, Xiaokang Yang Human-Aligned Image Models Improve Visual Decoding from the Brain
Nona Rajabi, Antonio H. Ribeiro, Miguel Vasco, Farzaneh Taleb, Mårten Björkman, Danica Kragic Hybrid Quantum-Classical Multi-Agent Pathfinding
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Zhenxing Mi, Kuan-Chieh Wang, Guocheng Qian, Hanrong Ye, Runtao Liu, Sergey Tulyakov, Kfir Aberman, Dan Xu IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck
Tian Bian, Yifan Niu, Chaohao Yuan, Chengzhi Piao, Bingzhe Wu, Long-Kai Huang, Yu Rong, Tingyang Xu, Hong Cheng, Jia Li Identifying Metric Structures of Deep Latent Variable Models
Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi, Benjamin Bloem-Reddy, Søren Hauberg Idiosyncrasies in Large Language Models
Mingjie Sun, Yida Yin, Zhiqiu Xu, J Zico Kolter, Zhuang Liu Imagine While Reasoning in Space: Multimodal Visualization-of-Thought
Chengzu Li, Wenshan Wu, Huanyu Zhang, Yan Xia, Shaoguang Mao, Li Dong, Ivan Vulić, Furu Wei Imitation Learning from a Single Temporally Misaligned Video
William Huey, Huaxiaoyue Wang, Anne Wu, Yoav Artzi, Sanjiban Choudhury IMPACT: Iterative Mask-Based Parallel Decoding for Text-to-Audio Generation with Diffusion Modeling
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Yuhang Cai, Kangjie Zhou, Jingfeng Wu, Song Mei, Michael Lindsey, Peter Bartlett Implicit Degree Bias in the Link Prediction Task
Rachith Aiyappa, Xin Wang, Munjung Kim, Ozgur Can Seckin, Yong-Yeol Ahn, Sadamori Kojaku Implicit Language Models Are RNNs: Balancing Parallelization and Expressivity
Mark Schöne, Babak Rahmani, Heiner Kremer, Fabian Falck, Hitesh Ballani, Jannes Gladrow Implicit Subgraph Neural Network
Yongjian Zhong, Liao Zhu, Hieu Vu, Bijaya Adhikari Importance Sampling for Nonlinear Models
Prakash Palanivelu Rajmohan, Fred Roosta Impossible Videos
Zechen Bai, Hai Ci, Mike Zheng Shou Improved Approximations for Hard Graph Problems Using Predictions
Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu Improved Learning via K-DTW: A Novel Dissimilarity Measure for Curves
Amer Krivošija, Alexander Munteanu, André Nusser, Chris Schwiegelshohn Improved Off-Policy Reinforcement Learning in Biological Sequence Design
Hyeonah Kim, Minsu Kim, Taeyoung Yun, Sanghyeok Choi, Emmanuel Bengio, Alex Hernández-Garcı́a, Jinkyoo Park Improving Consistency Models with Generator-Augmented Flows
Thibaut Issenhuth, Sangchul Lee, Ludovic Dos Santos, Jean-Yves Franceschi, Chansoo Kim, Alain Rakotomamonjy Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers
Filip Szatkowski, Yaoyue Zheng, Fei Yang, Tomasz Trzcinski, Bartłomiej Twardowski, Joost Van De Weijer Improving Diversity in Language Models: When Temperature Fails, Change the Loss
Alexandre Verine, Florian Le Bronnec, Kunhao Zheng, Alexandre Allauzen, Yann Chevaleyre, Benjamin Negrevergne Improving Flow Matching by Aligning Flow Divergence
Yuhao Huang, Taos Transue, Shih-Hsin Wang, William M Feldman, Hong Zhang, Bao Wang Improving Generalization with Flat Hilbert Bayesian Inference
Tuan Truong, Quyen Tran, Ngoc-Quan Pham, Nhat Ho, Dinh Phung, Trung Le Improving LLM Safety Alignment with Dual-Objective Optimization
Xuandong Zhao, Will Cai, Tianneng Shi, David Huang, Licong Lin, Song Mei, Dawn Song Improving LLM Video Understanding with 16 Frames per Second
Yixuan Li, Changli Tang, Jimin Zhuang, Yudong Yang, Guangzhi Sun, Wei Li, Zejun Ma, Chao Zhang Improving LLMs for Recommendation with Out-of-Vocabulary Tokens
Ting-Ji Huang, Jia-Qi Yang, Chunxu Shen, Kai-Qi Liu, De-Chuan Zhan, Han-Jia Ye Improving Model Alignment Through Collective Intelligence of Open-Source Models
Junlin Wang, Roy Xie, Shang Zhu, Jue Wang, Ben Athiwaratkun, Bhuwan Dhingra, Shuaiwen Leon Song, Ce Zhang, James Zou Improving Parallel Program Performance with LLM Optimizers via Agent-System Interfaces
Anjiang Wei, Allen Nie, Thiago S. F. X. Teixeira, Rohan Yadav, Wonchan Lee, Ke Wang, Alex Aiken Improving the Diffusability of Autoencoders
Ivan Skorokhodov, Sharath Girish, Benran Hu, Willi Menapace, Yanyu Li, Rameen Abdal, Sergey Tulyakov, Aliaksandr Siarohin Improving the Effective Receptive Field of Message-Passing Neural Networks
Shahaf E. Finder, Ron Shapira Weber, Moshe Eliasof, Oren Freifeld, Eran Treister Improving the Scaling Laws of Synthetic Data with Deliberate Practice
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Antoine Dedieu, Joseph Ortiz, Xinghua Lou, Carter Wendelken, J Swaroop Guntupalli, Wolfgang Lehrach, Miguel Lazaro-Gredilla, Kevin Patrick Murphy Improving Your Model Ranking on Chatbot Arena by Vote Rigging
Rui Min, Tianyu Pang, Chao Du, Qian Liu, Minhao Cheng, Min Lin In-Context Adaptation to Concept Drift for Learned Database Operations
Jiaqi Zhu, Shaofeng Cai, Yanyan Shen, Gang Chen, Fang Deng, Beng Chin Ooi In-Context Deep Learning via Transformer Models
Weimin Wu, Maojiang Su, Jerry Yao-Chieh Hu, Zhao Song, Han Liu In-Context Learning and Occam’s Razor
Eric Elmoznino, Tom Marty, Tejas Kasetty, Leo Gagnon, Sarthak Mittal, Mahan Fathi, Dhanya Sridhar, Guillaume Lajoie In-Context Learning as Conditioned Associative Memory Retrieval
Weimin Wu, Teng-Yun Hsiao, Jerry Yao-Chieh Hu, Wenxin Zhang, Han Liu In-Context Reinforcement Learning from Suboptimal Historical Data
Juncheng Dong, Moyang Guo, Ethan X Fang, Zhuoran Yang, Vahid Tarokh Independence Tests for Language Models
Sally Zhu, Ahmed M Ahmed, Rohith Kuditipudi, Percy Liang Inductive Moment Matching
Linqi Zhou, Stefano Ermon, Jiaming Song InfAlign: Inference-Aware Language Model Alignment
Ananth Balashankar, Ziteng Sun, Jonathan Berant, Jacob Eisenstein, Michael Collins, Adrian Hutter, Jong Lee, Chirag Nagpal, Flavien Prost, Aradhana Sinha, Ananda Theertha Suresh, Ahmad Beirami Inference-Time Alignment of Diffusion Models with Direct Noise Optimization
Zhiwei Tang, Jiangweizhi Peng, Jiasheng Tang, Mingyi Hong, Fan Wang, Tsung-Hui Chang Info-Coevolution: An Efficient Framework for Data Model Coevolution
Ziheng Qin, Hailun Xu, Wei Chee Yew, Qi Jia, Yang Luo, Kanchan Sarkar, Danhui Guan, Kai Wang, Yang You InfoSAM: Fine-Tuning the Segment Anything Model from an Information-Theoretic Perspective
Yuanhong Zhang, Muyao Yuan, Weizhan Zhang, Tieliang Gong, Wen Wen, Jiangyong Ying, Weijie Shi INRFlow: Flow Matching for INRs in Ambient Space
Yuyang Wang, Anurag Ranjan, Joshua M. Susskind, Miguel Ángel Bautista Instance Correlation Graph-Based Naive Bayes
Chengyuan Li, Liangxiao Jiang, Wenjun Zhang, Liangjun Yu, Huan Zhang Instruction-Following Pruning for Large Language Models
Bairu Hou, Qibin Chen, Jianyu Wang, Guoli Yin, Chong Wang, Nan Du, Ruoming Pang, Shiyu Chang, Tao Lei Integer Programming for Generalized Causal Bootstrap Designs
Jennifer Rogers Brennan, Sebastien Lahaie, Adel Javanmard, Nick Doudchenko, Jean Pouget-Abadie Integration-Free Kernels for Equivariant Gaussian Process Modelling
Tim Steinert, David Ginsbourger, August Lykke-Møller, Ove Christiansen, Henry Moss Interaction-Aware Gaussian Weighting for Clustered Federated Learning
Alessandro Licciardi, Davide Leo, Eros Fanı̀, Barbara Caputo, Marco Ciccone Interpreting CLIP with Hierarchical Sparse Autoencoders
Vladimir Zaigrajew, Hubert Baniecki, Przemyslaw Biecek Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces
Eric Eaton, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell Introducing 3D Representation for Dense Volume-to-Volume Translation via Score Fusion
Xiyue Zhu, Dou Hoon Kwark, Ruike Zhu, Kaiwen Hong, Yiqi Tao, Shirui Luo, Yudu Li, Zhi-Pei Liang, Volodymyr Kindratenko Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning
Changsheng Wang, Yihua Zhang, Jinghan Jia, Parikshit Ram, Dennis Wei, Yuguang Yao, Soumyadeep Pal, Nathalie Baracaldo, Sijia Liu Inverse Bridge Matching Distillation
Nikita Gushchin, David Li, Daniil Selikhanovych, Evgeny Burnaev, Dmitry Baranchuk, Alexander Korotin Inverse Optimization via Learning Feasible Regions
Ke Ren, Peyman Mohajerin Esfahani, Angelos Georghiou Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo
Idan Achituve, Hai Victor Habi, Amir Rosenfeld, Arnon Netzer, Idit Diamant, Ethan Fetaya Inverse Problems with Experiment-Guided AlphaFold
Sai Advaith Maddipatla, Nadav Bojan, Meital Bojan, Sanketh Vedula, Paul Schanda, Ailie Marx, Alexander Bronstein Investigating Non-Transitivity in LLM-as-a-Judge
Yi Xu, Laura Ruis, Tim Rocktäschel, Robert Kirk Investigating the Overlooked Hessian Structure: From CNNs to LLMs
Qian-Yuan Tang, Yufei Gu, Yunfeng Cai, Mingming Sun, Ping Li, Zhou Xun, Zeke Xie Is Complex Query Answering Really Complex?
Cosimo Gregucci, Bo Xiong, Daniel Hernández, Lorenzo Loconte, Pasquale Minervini, Steffen Staab, Antonio Vergari Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs
Yinong Oliver Wang, Nivedha Sivakumar, Falaah Arif Khan, Katherine Metcalf, Adam Golinski, Natalie Mackraz, Barry-John Theobald, Luca Zappella, Nicholas Apostoloff Isolated Causal Effects of Natural Language
Victoria Lin, Louis-Philippe Morency, Eli Ben-Michael IT$^3$: Idempotent Test-Time Training
Nikita Durasov, Assaf Shocher, Doruk Oner, Gal Chechik, Alexei A Efros, Pascal Fua ITBench: Evaluating AI Agents Across Diverse Real-World IT Automation Tasks
Saurabh Jha, Rohan R. Arora, Yuji Watanabe, Takumi Yanagawa, Yinfang Chen, Jackson Clark, Bhavya Bhavya, Mudit Verma, Harshit Kumar, Hirokuni Kitahara, Noah Zheutlin, Saki Takano, Divya Pathak, Felix George, Xinbo Wu, Bekir O Turkkan, Gerard Vanloo, Michael Nidd, Ting Dai, Oishik Chatterjee, Pranjal Gupta, Suranjana Samanta, Pooja Aggarwal, Rong Lee, Jae-Wook Ahn, Debanjana Kar, Amit Paradkar, Yu Deng, Pratibha Moogi, Prateeti Mohapatra, Naoki Abe, Chandrasekhar Narayanaswami, Tianyin Xu, Lav R. Varshney, Ruchi Mahindru, Anca Sailer, Laura Shwartz, Daby Sow, Nicholas C. M. Fuller, Ruchir Puri ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset
Yilin Wang, Peixuan Lei, Jie Song, Yuzhe Hao, Tao Chen, Yuxuan Zhang, Lei Jia, Yuanxiang Li, Zhongyu Wei Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient
Jan Ludziejewski, Maciej Pióro, Jakub Krajewski, Maciej Stefaniak, Michał Krutul, Jan Małaśnicki, Marek Cygan, Piotr Sankowski, Kamil Adamczewski, Piotr Miłoś, Sebastian Jaszczur KABB: Knowledge-Aware Bayesian Bandits for Dynamic Expert Coordination in Multi-Agent Systems
Jusheng Zhang, Zimeng Huang, Yijia Fan, Ningyuan Liu, Mingyan Li, Zhuojie Yang, Jiawei Yao, Jian Wang, Keze Wang KAN-AD: Time Series Anomaly Detection with Kolmogorov–Arnold Networks
Quan Zhou, Changhua Pei, Fei Sun, Han Jing, Zhengwei Gao, Haiming Zhang, Gaogang Xie, Dan Pei, Jianhui Li KBQA-O1: Agentic Knowledge Base Question Answering with Monte Carlo Tree Search
Haoran Luo, Haihong E, Yikai Guo, Qika Lin, Xiaobao Wu, Xinyu Mu, Wenhao Liu, Meina Song, Yifan Zhu, Anh Tuan Luu Kernel Quantile Embeddings and Associated Probability Metrics
Masha Naslidnyk, Siu Lun Chau, Francois-Xavier Briol, Krikamol Muandet KernelBench: Can LLMs Write Efficient GPU Kernels?
Anne Ouyang, Simon Guo, Simran Arora, Alex L Zhang, William Hu, Christopher Re, Azalia Mirhoseini KGMark: A Diffusion Watermark for Knowledge Graphs
Hongrui Peng, Haolang Lu, Yuanlong Yu, Weiye Fu, Kun Wang, Guoshun Nan KinDEL: DNA-Encoded Library Dataset for Kinase Inhibitors
Benson Chen, Tomasz Danel, Gabriel H. S. Dreiman, Patrick J. Mcenaney, Nikhil Jain, Kirill Novikov, Spurti Umesh Akki, Joshua L. Turnbull, Virja Atul Pandya, Boris P. Belotserkovskii, Jared Bryce Weaver, Ankita Biswas, Dat Nguyen, Kent Gorday, Mohammad Sultan, Nathaniel Stanley, Daniel M Whalen, Divya Kanichar, Christoph Klein, Emily Fox, R. Edward Watts Kinetic Langevin Diffusion for Crystalline Materials Generation
François R J Cornet, Federico Bergamin, Arghya Bhowmik, Juan Maria Garcia-Lastra, Jes Frellsen, Mikkel N. Schmidt Knowledge Swapping via Learning and Unlearning
Mingyu Xing, Lechao Cheng, Shengeng Tang, Yaxiong Wang, Zhun Zhong, Meng Wang L-Diffusion: Laplace Diffusion for Efficient Pathology Image Segmentation
Weihan Li, Linyun Zhou, Jian Yang, Shengxuming Zhang, Xiangtong Du, Xiuming Zhang, Jing Zhang, Chaoqing Xu, Mingli Song, Zunlei Feng L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning
Xiang Zhang, Run He, Chen Jiao, Di Fang, Ming Li, Ziqian Zeng, Cen Chen, Huiping Zhuang La RoSA: Enhancing LLM Efficiency via Layerwise Rotated Sparse Activation
Kai Liu, Bowen Xu, Shaoyu Wu, Xin Chen, Hao Zhou, Yongliang Tao, Lulu Hu LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models
Dachuan Shi, Yonggan Fu, Xiangchi Yuan, Zhongzhi Yu, Haoran You, Sixu Li, Xin Dong, Jan Kautz, Pavlo Molchanov, Yingyan Celine Lin Ladder-Residual: Parallelism-Aware Architecture for Accelerating Large Model Inference with Communication Overlapping
Muru Zhang, Mayank Mishra, Zhongzhu Zhou, William Brandon, Jue Wang, Yoon Kim, Jonathan Ragan-Kelley, Shuaiwen Leon Song, Ben Athiwaratkun, Tri Dao LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models
Fanfei Li, Thomas Klein, Wieland Brendel, Robert Geirhos, Roland S. Zimmermann Language Models as Implicit Tree Search
Ziliang Chen, Zhao-Rong Lai, Yufeng Yang, Liangda Fang, Zhanfu Yang, Liang Lin Language Models May Verbatim Complete Text They Were Not Explicitly Trained on
Ken Liu, Christopher A. Choquette-Choo, Matthew Jagielski, Peter Kairouz, Sanmi Koyejo, Percy Liang, Nicolas Papernot Language Models over Canonical Byte-Pair Encodings
Tim Vieira, Tianyu Liu, Clemente Pasti, Yahya Emara, Brian Dusell, Benjamin Lebrun, Mario Giulianelli, Juan Luis Gastaldi, Timothy J. O’Donnell, Ryan Cotterell Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups
Vladimir R Kostic, Karim Lounici, Hélène Halconruy, Timothée Devergne, Pietro Novelli, Massimiliano Pontil Large Continual Instruction Assistant
Jingyang Qiao, Zhizhong Zhang, Xin Tan, Yanyun Qu, Shouhong Ding, Yuan Xie Large Language Models Are Demonstration Pre-Selectors for Themselves
Jiarui Jin, Yuwei Wu, Haoxuan Li, Xiaoting He, Weinan Zhang, Yiming Yang, Yong Yu, Jun Wang, Mengyue Yang Large Language-Geometry Model: When LLM Meets Equivariance
Zongzhao Li, Jiacheng Cen, Bing Su, Tingyang Xu, Yu Rong, Deli Zhao, Wenbing Huang Larger or Smaller Reward Margins to Select Preferences for LLM Alignment?
Kexin Huang, Junkang Wu, Ziqian Chen, Xue Wang, Jinyang Gao, Bolin Ding, Jiancan Wu, Xiangnan He, Xiang Wang LAST SToP for Modeling Asynchronous Time Series
Shubham Gupta, Thibaut Durand, Graham W. Taylor, Lilian Bialokozowicz Latent Action Learning Requires Supervision in the Presence of Distractors
Alexander Nikulin, Ilya Zisman, Denis Tarasov, Lyubaykin Nikita, Andrei Polubarov, Igor Kiselev, Vladislav Kurenkov Latent Diffusion Planning for Imitation Learning
Amber Xie, Oleh Rybkin, Dorsa Sadigh, Chelsea Finn Latent Mamba Operator for Partial Differential Equations
Karn Tiwari, Niladri Dutta, N M Anoop Krishnan, Prathosh Ap Latent Score-Based Reweighting for Robust Classification on Imbalanced Tabular Data
Yunze Tong, Fengda Zhang, Zihao Tang, Kaifeng Gao, Kai Huang, Pengfei Lyu, Jun Xiao, Kun Kuang Latent Thought Models with Variational Bayes Inference-Time Computation
Deqian Kong, Minglu Zhao, Dehong Xu, Bo Pang, Shu Wang, Edouardo Honig, Zhangzhang Si, Chuan Li, Jianwen Xie, Sirui Xie, Ying Nian Wu Latent Variable Causal Discovery Under Selection Bias
Haoyue Dai, Yiwen Qiu, Ignavier Ng, Xinshuai Dong, Peter Spirtes, Kun Zhang Latent Variable Estimation in Bayesian Black-Litterman Models
Thomas Yuan-Lung Lin, Jerry Yao-Chieh Hu, Paul W. Chiou, Peter Lin LAuReL: Learned Augmented Residual Layer
Gaurav Menghani, Ravi Kumar, Sanjiv Kumar Layer by Layer: Uncovering Hidden Representations in Language Models
Oscar Skean, Md Rifat Arefin, Dan Zhao, Niket Nikul Patel, Jalal Naghiyev, Yann Lecun, Ravid Shwartz-Ziv Layer-Wise Alignment: Examining Safety Alignment Across Image Encoder Layers in Vision Language Models
Saketh Bachu, Erfan Shayegani, Rohit Lal, Trishna Chakraborty, Arindam Dutta, Chengyu Song, Yue Dong, Nael B. Abu-Ghazaleh, Amit Roy-Chowdhury Layer-Wise Quantization for Quantized Optimistic Dual Averaging
Anh Duc Nguyen, Ilia Markov, Zhengqing Wu, Ali Ramezani-Kebrya, Kimon Antonakopoulos, Dan Alistarh, Volkan Cevher LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width Allocation
Li Ding, Hao Zhang, Wenrui Dai, Chenglin Li, Weijia Lu, Zhifei Yang, Xiaodong Zhang, Xiaofeng Ma, Junni Zou, Hongkai Xiong Learn Beneficial Noise as Graph Augmentation
Siqi Huang, Yanchen Xu, Hongyuan Zhang, Xuelong Li Learn from Downstream and Be Yourself in Multimodal Large Language Models Fine-Tuning
Wenke Huang, Jian Liang, Zekun Shi, Didi Zhu, Guancheng Wan, He Li, Bo Du, Dacheng Tao, Mang Ye Learnable Spatial-Temporal Positional Encoding for Link Prediction
Katherine Tieu, Dongqi Fu, Zihao Li, Ross Maciejewski, Jingrui He Learning Adaptive Lighting via Channel-Aware Guidance
Qirui Yang, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Bo Li, Huanjing Yue, Jingyu Yang Learning Adversarial MDPs with Stochastic Hard Constraints
Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti Learning Bayesian Nash Equilibrium in Auction Games via Approximate Best Response
Kexin Huang, Ziqian Chen, Xue Wang, Chongming Gao, Jinyang Gao, Bolin Ding, Xiang Wang Learning Cascade Ranking as One Network
Yunli Wang, Zhen Zhang, Zhiqiang Wang, Zixuan Yang, Yu Li, Jian Yang, Shiyang Wen, Peng Jiang, Kun Gai Learning Classifiers That Induce Markets
Yonatan Sommer, Ivri Hikri, Lotan Amit, Nir Rosenfeld Learning Distances from Data with Normalizing Flows and Score Matching
Peter Sorrenson, Daniel Behrend-Uriarte, Christoph Schnoerr, Ullrich Koethe Learning Dynamics in Linear Recurrent Neural Networks
Alexandra Maria Proca, Clémentine Carla Juliette Dominé, Murray Shanahan, Pedro A. M. Mediano Learning Efficient Robotic Garment Manipulation with Standardization
Changshi Zhou, Feng Luan, Jiarui Hu, Shaoqiang Meng, Zhipeng Wang, Yanchao Dong, Yanmin Zhou, Bin He Learning Gaussian DAG Models Without Condition Number Bounds
Constantinos Costis Daskalakis, Anthimos Vardis Kandiros, Rui Yao Learning Imbalanced Data with Beneficial Label Noise
Guangzheng Hu, Feng Liu, Mingming Gong, Guanghui Wang, Liuhua Peng Learning Invariant Causal Mechanism from Vision-Language Models
Zeen Song, Siyu Zhao, Xingyu Zhang, Jiangmeng Li, Changwen Zheng, Wenwen Qiang Learning Likelihood-Free Reference Priors
Nicholas George Bishop, Daniel Jarne Ornia, Joel Dyer, Ani Calinescu, Michael J. Wooldridge Learning Minimum-Size BDDs: Towards Efficient Exact Algorithms
Christian Komusiewicz, Andre Schidler, Frank Sommer, Manuel Sorge, Luca Pascal Staus Learning Monotonic Probabilities with a Generative Cost Model
Yongxiang Tang, Yanhua Cheng, Xiaocheng Liu, Chenchen Jiao, Yanxiang Zeng, Ning Luo, Pengjia Yuan, Xialong Liu, Peng Jiang Learning Multivariate Gaussians with Imperfect Advice
Arnab Bhattacharyya, Davin Choo, Philips George John, Themis Gouleakis Learning Policy Committees for Effective Personalization in MDPs with Diverse Tasks
Luise Ge, Michael Lanier, Anindya Sarkar, Bengisu Guresti, Chongjie Zhang, Yevgeniy Vorobeychik Learning Representations of Instruments for Partial Identification of Treatment Effects
Jonas Schweisthal, Dennis Frauen, Maresa Schröder, Konstantin Hess, Niki Kilbertus, Stefan Feuerriegel Learning Robust Neural Processes with Risk-Averse Stochastic Optimization
Huafeng Liu, Yiran Fu, Liping Jing, Hui Li, Shuyang Lin, Jingyue Shi, Deqiang Ouyang, Jian Yu Learning Safe Control via On-the-Fly Bandit Exploration
Alexandre Capone, Ryan Kazuo Cosner, Aaron Ames, Sandra Hirche Learning Single Index Models with Diffusion Priors
Anqi Tang, Youming Chen, Shuchen Xue, Zhaoqiang Liu Learning Smooth and Expressive Interatomic Potentials for Physical Property Prediction
Xiang Fu, Brandon M Wood, Luis Barroso-Luque, Daniel S. Levine, Meng Gao, Misko Dzamba, C. Lawrence Zitnick Learning Soft Sparse Shapes for Efficient Time-Series Classification
Zhen Liu, Yicheng Luo, Boyuan Li, Emadeldeen Eldele, Min Wu, Qianli Ma Learning the Electronic Hamiltonian of Large Atomic Structures
Chen Hao Xia, Manasa Kaniselvan, Alexandros Nikolaos Ziogas, Marko Mladenović, Rayen Mahjoub, Alexander Maeder, Mathieu Luisier Learning the RoPEs: Better 2D and 3D Position Encodings with STRING
Connor Schenck, Isaac Reid, Mithun George Jacob, Alex Bewley, Joshua Ainslie, David Rendleman, Deepali Jain, Mohit Sharma, Kumar Avinava Dubey, Ayzaan Wahid, Sumeet Singh, René Wagner, Tianli Ding, Chuyuan Fu, Arunkumar Byravan, Jake Varley, Alexey A. Gritsenko, Matthias Minderer, Dmitry Kalashnikov, Jonathan Tompson, Vikas Sindhwani, Krzysztof Marcin Choromanski Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Yu Sun, Xinhao Li, Karan Dalal, Jiarui Xu, Arjun Vikram, Genghan Zhang, Yann Dubois, Xinlei Chen, Xiaolong Wang, Sanmi Koyejo, Tatsunori Hashimoto, Carlos Guestrin Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding
Tian Jin, Ellie Y Cheng, Zachary Ankner, Nikunj Saunshi, Blake M Elias, Amir Yazdanbakhsh, Jonathan Ragan-Kelley, Suvinay Subramanian, Michael Carbin Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge
Swarnadeep Saha, Xian Li, Marjan Ghazvininejad, Jason E Weston, Tianlu Wang Learning to Reuse Policies in State Evolvable Environments
Ziqian Zhang, Bohan Yang, Lihe Li, Yuqi Bian, Ruiqi Xue, Feng Chen, Yi-Chen Li, Lei Yuan, Yang Yu Learning to Route LLMs with Confidence Tokens
Yu-Neng Chuang, Prathusha Kameswara Sarma, Parikshit Gopalan, John Boccio, Sara Bolouki, Xia Hu, Helen Zhou Learning to Steer Learners in Games
Yizhou Zhang, Yian Ma, Eric Mazumdar Learning Vision and Language Concepts for Controllable Image Generation
Shaoan Xie, Lingjing Kong, Yujia Zheng, Zeyu Tang, Eric Xing, Guangyi Chen, Kun Zhang Learning with Exact Invariances in Polynomial Time
Ashkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka, Patrick Jaillet Learning Without Isolation: Pathway Protection for Continual Learning
Zhikang Chen, Abudukelimu Wuerkaixi, Sen Cui, Haoxuan Li, Ding Li, Jingfeng Zhang, Bo Han, Gang Niu, Houfang Liu, Yi Yang, Sifan Yang, Changshui Zhang, Tianling Ren Learning-Augmented Hierarchical Clustering
Vladimir Braverman, Jon C. Ergun, Chen Wang, Samson Zhou Learnings from Scaling Visual Tokenizers for Reconstruction and Generation
Philippe Hansen-Estruch, David Yan, Ching-Yao Chuang, Orr Zohar, Jialiang Wang, Tingbo Hou, Tao Xu, Sriram Vishwanath, Peter Vajda, Xinlei Chen Learnware Specification via Dual Alignment
Wei Chen, Jun-Xiang Mao, Xiaozheng Wang, Min-Ling Zhang LEMoN: Label Error Detection Using Multimodal Neighbors
Haoran Zhang, Aparna Balagopalan, Nassim Oufattole, Hyewon Jeong, Yan Wu, Jiacheng Zhu, Marzyeh Ghassemi LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
Xinyue Zeng, Haohui Wang, Junhong Lin, Jun Wu, Tyler Cody, Dawei Zhou Let LLM Tell What to Prune and How Much to Prune
Mingzhe Yang, Sihao Lin, Changlin Li, Xiaojun Chang LETS Forecast: Learning Embedology for Time Series Forecasting
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi Gnvv, Nada Magdi Elkordi, Yin Li Leveraging Per-Instance Privacy for Machine Unlearning
Nazanin Mohammadi Sepahvand, Anvith Thudi, Berivan Isik, Ashmita Bhattacharyya, Nicolas Papernot, Eleni Triantafillou, Daniel M. Roy, Gintare Karolina Dziugaite Leveraging Predictive Equivalence in Decision Trees
Hayden Mctavish, Zachery Boner, Jon Donnelly, Margo Seltzer, Cynthia Rudin LEVIS: Large Exact Verifiable Input Spaces for Neural Networks
Mohamad Fares El Hajj Chehade, Wenting Li, Brian Wesley Bell, Russell Bent, Saif R. Kazi, Hao Zhu LieRE: Lie Rotational Positional Encodings
Sophie Ostmeier, Brian Axelrod, Maya Varma, Michael Moseley, Akshay S Chaudhari, Curtis Langlotz LightGTS: A Lightweight General Time Series Forecasting Model
Yihang Wang, Yuying Qiu, Peng Chen, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo Lightweight Online Adaption for Time Series Foundation Model Forecasts
Thomas L Lee, William Toner, Rajkarn Singh, Artjom Joosen, Martin Asenov Lightweight Protocols for Distributed Private Quantile Estimation
Anders Aamand, Fabrizio Boninsegna, Abigail Gentle, Jacob Imola, Rasmus Pagh Linear Bandits with Partially Observable Features
Wonyoung Kim, Sungwoo Park, Garud Iyengar, Assaf Zeevi, Min-Hwan Oh LipsNet++: Unifying Filter and Controller into a Policy Network
Xujie Song, Liangfa Chen, Tong Liu, Wenxuan Wang, Yinuo Wang, Shentao Qin, Yinsong Ma, Jingliang Duan, Shengbo Eben Li LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces
Rashid Mushkani, Shravan Nayak, Hugo Berard, Allison Cohen, Shin Koseki, Hadrien Bertrand LlavaGuard: An Open VLM-Based Framework for Safeguarding Vision Datasets and Models
Lukas Helff, Felix Friedrich, Manuel Brack, Kristian Kersting, Patrick Schramowski LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
Bowen Jin, Jinsung Yoon, Zhen Qin, Ziqi Wang, Wei Xiong, Yu Meng, Jiawei Han, Sercan O Arik LLM Data Selection and Utilization via Dynamic Bi-Level Optimization
Yang Yu, Kai Han, Hang Zhou, Yehui Tang, Kaiqi Huang, Yunhe Wang, Dacheng Tao LLM-Augmented Chemical Synthesis and Design Decision Programs
Haorui Wang, Jeff Guo, Lingkai Kong, Rampi Ramprasad, Philippe Schwaller, Yuanqi Du, Chao Zhang LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models
Parshin Shojaee, Ngoc-Hieu Nguyen, Kazem Meidani, Amir Barati Farimani, Khoa D Doan, Chandan K. Reddy LLMs Can Reason Faster Only if We Let Them
Bilgehan Sel, Lifu Huang, Naren Ramakrishnan, Ruoxi Jia, Ming Jin LLMs Can See and Hear Without Any Training
Kumar Ashutosh, Yossi Gandelsman, Xinlei Chen, Ishan Misra, Rohit Girdhar LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws
Prasanna Mayilvahanan, Thaddäus Wiedemer, Sayak Mallick, Matthias Bethge, Wieland Brendel LLMScan: Causal Scan for LLM Misbehavior Detection
Mengdi Zhang, Goh Kai Kiat, Peixin Zhang, Jun Sun, Lin Xin Rose, Hongyu Zhang LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models
Marwa Abdulhai, Isadora White, Charlie Victor Snell, Charles Sun, Joey Hong, Yuexiang Zhai, Kelvin Xu, Sergey Levine LOB-Bench: Benchmarking Generative AI for Finance - An Application to Limit Order Book Data
Peer Nagy, Sascha Yves Frey, Kang Li, Bidipta Sarkar, Svitlana Vyetrenko, Stefan Zohren, Ani Calinescu, Jakob Nicolaus Foerster Local Pan-Privacy for Federated Analytics
Vitaly Feldman, Audra Mcmillan, Guy N. Rothblum, Kunal Talwar LOCATE 3D: Real-World Object Localization via Self-Supervised Learning in 3D
Paul Mcvay, Sergio Arnaud, Ada Martin, Arjun Majumdar, Krishna Murthy Jatavallabhula, Phillip Thomas, Ruslan Partsey, Daniel Dugas, Abha Gejji, Alexander Sax, Vincent-Pierre Berges, Mikael Henaff, Ayush Jain, Ang Cao, Ishita Prasad, Mrinal Kalakrishnan, Michael Rabbat, Nicolas Ballas, Mido Assran, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier Locate-Then-Edit for Multi-Hop Factual Recall Under Knowledge Editing
Zhuoran Zhang, Yongxiang Li, Zijian Kan, Keyuan Cheng, Lijie Hu, Di Wang Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning
Armin Behnamnia, Gholamali Aminian, Alireza Aghaei, Chengchun Shi, Vincent Tan, Hamid R. Rabiee Logits Are All We Need to Adapt Closed Models
Gaurush Hiranandani, Haolun Wu, Subhojyoti Mukherjee, Sanmi Koyejo Long-Form Speech Generation with Spoken Language Models
Se Jin Park, Julian Salazar, Aren Jansen, Keisuke Kinoshita, Yong Man Ro, Rj Skerry-Ryan Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model
Fei Shen, Cong Wang, Junyao Gao, Qin Guo, Jisheng Dang, Jinhui Tang, Tat-Seng Chua LongRoPE2: Near-Lossless LLM Context Window Scaling
Ning Shang, Li Lyna Zhang, Siyuan Wang, Gaokai Zhang, Gilsinia Lopez, Fan Yang, Weizhu Chen, Mao Yang LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding
Xiaoqian Shen, Yunyang Xiong, Changsheng Zhao, Lemeng Wu, Jun Chen, Chenchen Zhu, Zechun Liu, Fanyi Xiao, Balakrishnan Varadarajan, Florian Bordes, Zhuang Liu, Hu Xu, Hyunwoo J. Kim, Bilge Soran, Raghuraman Krishnamoorthi, Mohamed Elhoseiny, Vikas Chandra Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models
Xin Zou, Yizhou Wang, Yibo Yan, Yuanhuiyi Lyu, Kening Zheng, Sirui Huang, Junkai Chen, Peijie Jiang, Jia Liu, Chang Tang, Xuming Hu Looking Beyond the Top-1: Transformers Determine Top Tokens in Order
Daria Lioubashevski, Tomer M. Schlank, Gabriel Stanovsky, Ariel Goldstein LoRA-Gen: Specializing Large Language Model via Online LoRA Generation
Yicheng Xiao, Lin Song, Rui Yang, Cheng Cheng, Yixiao Ge, Xiu Li, Ying Shan Loss Functions and Operators Generated by F-Divergences
Vincent Roulet, Tianlin Liu, Nino Vieillard, Michael Eli Sander, Mathieu Blondel Low-Rank Thinning
Annabelle Michael Carrell, Albert Gong, Abhishek Shetty, Raaz Dwivedi, Lester Mackey LSCD: Lomb–Scargle Conditioned Diffusion for Time Series Imputation
Elizabeth Fons, Alejandro Sztrajman, Yousef El-Laham, Luciana Ferrer, Svitlana Vyetrenko, Manuela Veloso M+: Extending MemoryLLM with Scalable Long-Term Memory
Yu Wang, Dmitry Krotov, Yuanzhe Hu, Yifan Gao, Wangchunshu Zhou, Julian Mcauley, Dan Gutfreund, Rogerio Feris, Zexue He MA-LoT: Model-Collaboration Lean-Based Long Chain-of-Thought Reasoning Enhances Formal Theorem Proving
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Jesse He, Helen Jenne, Herman Chau, Davis Brown, Mark Raugas, Sara C. Billey, Henry Kvinge MAGELLAN: Metacognitive Predictions of Learning Progress Guide Autotelic LLM Agents in Large Goal Spaces
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Sushant Agarwal, Amit Deshpande, Rajmohan Rajaraman, Ravi Sundaram Optimal Information Retention for Time-Series Explanations
Jinghang Yue, Jing Wang, Lu Zhang, Shuo Zhang, Da Li, Zhaoyang Ma, Youfang Lin Optimal Transfer Learning for Missing Not-at-Random Matrix Completion
Akhil Jalan, Yassir Jedra, Arya Mazumdar, Soumendu Sundar Mukherjee, Purnamrita Sarkar Optimal Transport-Based Conformal Prediction
Gauthier Thurin, Kimia Nadjahi, Claire Boyer Optimization for Neural Operators Can Benefit from Width
Pedro Cisneros-Velarde, Bhavesh Shrimali, Arindam Banerjee Optimizing Large Language Model Training Using FP4 Quantization
Ruizhe Wang, Yeyun Gong, Xiao Liu, Guoshuai Zhao, Ziyue Yang, Baining Guo, Zheng-Jun Zha, Peng Cheng Optimizing Noise Distributions for Differential Privacy
Atefeh Gilani, Juan Felipe Gomez, Shahab Asoodeh, Flavio Calmon, Oliver Kosut, Lalitha Sankar Optimizing Social Network Interventions via Hypergradient-Based Recommender System Design
Marino Kühne, Panagiotis D. Grontas, Giulia De Pasquale, Giuseppe Belgioioso, Florian Dorfler, John Lygeros Optimizing Test-Time Compute via Meta Reinforcement Finetuning
Yuxiao Qu, Matthew Y. R. Yang, Amrith Setlur, Lewis Tunstall, Edward Emanuel Beeching, Ruslan Salakhutdinov, Aviral Kumar Oracle-MoE: Locality-Preserving Routing in the Oracle Space for Memory-Constrained Large Language Model Inference
Jixian Zhou, Fang Dong, Ruijun Huang, Hengjie Cao, Mengyi Chen, Yifeng Yang, Anrui Chen, Mingzhi Dong, Yujiang Wang, Dongsheng Li, David A. Clifton, Qin Lv, Rui Zhu, Chun Zhang, Fan Yang, Tun Lu, Ning Gu, Li Shang OrcaLoca: An LLM Agent Framework for Software Issue Localization
Zhongming Yu, Hejia Zhang, Yujie Zhao, Hanxian Huang, Matrix Yao, Ke Ding, Jishen Zhao Organize the Web: Constructing Domains Enhances Pre-Training Data Curation
Alexander Wettig, Kyle Lo, Sewon Min, Hannaneh Hajishirzi, Danqi Chen, Luca Soldaini Origin Identification for Text-Guided Image-to-Image Diffusion Models
Wenhao Wang, Yifan Sun, Zongxin Yang, Zhentao Tan, Zhengdong Hu, Yi Yang Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detection
Zhiyuan Yan, Jiangming Wang, Peng Jin, Ke-Yue Zhang, Chengchun Liu, Shen Chen, Taiping Yao, Shouhong Ding, Baoyuan Wu, Li Yuan Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads
Siqi Kou, Jiachun Jin, Zhihong Liu, Chang Liu, Ye Ma, Jian Jia, Quan Chen, Peng Jiang, Zhijie Deng OTTER: A Vision-Language-Action Model with Text-Aware Visual Feature Extraction
Huang Huang, Fangchen Liu, Letian Fu, Tingfan Wu, Mustafa Mukadam, Jitendra Malik, Ken Goldberg, Pieter Abbeel Otter: Generating Tests from Issues to Validate SWE Patches
Toufique Ahmed, Jatin Ganhotra, Rangeet Pan, Avraham Shinnar, Saurabh Sinha, Martin Hirzel Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models
Siddarth Venkatraman, Mohsin Hasan, Minsu Kim, Luca Scimeca, Marcin Sendera, Yoshua Bengio, Glen Berseth, Nikolay Malkin OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition
Zheng Lian, Haiyang Sun, Licai Sun, Haoyu Chen, Lan Chen, Hao Gu, Zhuofan Wen, Shun Chen, Zhang Siyuan, Hailiang Yao, Bin Liu, Rui Liu, Shan Liang, Ya Li, Jiangyan Yi, Jianhua Tao Over-Tokenized Transformer: Vocabulary Is Generally Worth Scaling
Hongzhi Huang, Defa Zhu, Banggu Wu, Yutao Zeng, Ya Wang, Qiyang Min, Zhou Xun Overcoming Multi-Step Complexity in Multimodal Theory-of-Mind Reasoning: A Scalable Bayesian Planner
Chunhui Zhang, Zhongyu Ouyang, Kwonjoon Lee, Nakul Agarwal, Sean Dae Houlihan, Soroush Vosoughi, Shao-Yuan Lo Overtrained Language Models Are Harder to Fine-Tune
Jacob Mitchell Springer, Sachin Goyal, Kaiyue Wen, Tanishq Kumar, Xiang Yue, Sadhika Malladi, Graham Neubig, Aditi Raghunathan OWLS: Scaling Laws for Multilingual Speech Recognition and Translation Models
William Chen, Jinchuan Tian, Yifan Peng, Brian Yan, Chao-Han Huck Yang, Shinji Watanabe P(all-Atom) Is Unlocking New Path for Protein Design
Wei Qu, Jiawei Guan, Rui Ma, Ke Zhai, Weikun Wu, Haobo Wang PAC Learning with Improvements
Idan Attias, Avrim Blum, Keziah Naggita, Donya Saless, Dravyansh Sharma, Matthew Walter PaperBench: Evaluating AI’s Ability to Replicate AI Research
Giulio Starace, Oliver Jaffe, Dane Sherburn, James Aung, Jun Shern Chan, Leon Maksin, Rachel Dias, Evan Mays, Benjamin Kinsella, Wyatt Thompson, Johannes Heidecke, Amelia Glaese, Tejal Patwardhan ParallelComp: Parallel Long-Context Compressor for Length Extrapolation
Jing Xiong, Jianghan Shen, Chuanyang Zheng, Zhongwei Wan, Chenyang Zhao, Chiwun Yang, Fanghua Ye, Hongxia Yang, Lingpeng Kong, Ngai Wong Parameter-Efficient Fine-Tuning of State Space Models
Kevin Galim, Wonjun Kang, Yuchen Zeng, Hyung Il Koo, Kangwook Lee Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models
Samira Abnar, Harshay Shah, Dan Busbridge, Alaaeldin El-Nouby, Joshua M. Susskind, Vimal Thilak PARQ: Piecewise-Affine Regularized Quantization
Lisa Jin, Jianhao Ma, Zechun Liu, Andrey Gromov, Aaron Defazio, Lin Xiao Parrot: Multilingual Visual Instruction Tuning
Hai-Long Sun, Da-Wei Zhou, Yang Li, Shiyin Lu, Chao Yi, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, De-Chuan Zhan, Han-Jia Ye PASS: Private Attributes Protection with Stochastic Data Substitution
Yizhuo Chen, Chun-Fu Chen, Hsiang Hsu, Shaohan Hu, Tarek F. Abdelzaher Patch-Wise Structural Loss for Time Series Forecasting
Dilfira Kudrat, Zongxia Xie, Yanru Sun, Tianyu Jia, Qinghua Hu PDE-Controller: LLMs for Autoformalization and Reasoning of PDEs
Mauricio Soroco, Jialin Song, Mengzhou Xia, Kye Emond, Weiran Sun, Wuyang Chen PDUDT: Provable Decentralized Unlearning Under Dynamic Topologies
Jing Qiao, Yu Liu, Zengzhe Chen, Mingyi Li, Yuan Yuan, Xiao Zhang, Dongxiao Yu Penalizing Infeasible Actions and Reward Scaling in Reinforcement Learning with Offline Data
Jeonghye Kim, Yongjae Shin, Whiyoung Jung, Sunghoon Hong, Deunsol Yoon, Youngchul Sung, Kanghoon Lee, Woohyung Lim PENCIL: Long Thoughts with Short Memory
Chenxiao Yang, Nathan Srebro, David Mcallester, Zhiyuan Li Perception in Reflection
Yana Wei, Liang Zhao, Kangheng Lin, En Yu, Yuang Peng, Runpei Dong, Jianjian Sun, Haoran Wei, Zheng Ge, Xiangyu Zhang, Vishal M. Patel Perceptually Constrained Precipitation Nowcasting Model
Wenzhi Feng, Xutao Li, Zhe Wu, Kenghong Lin, Demin Yu, Yunming Ye, Yaowei Wang Peri-LN: Revisiting Normalization Layer in the Transformer Architecture
Jeonghoon Kim, Byeongchan Lee, Cheonbok Park, Yeontaek Oh, Beomjun Kim, Taehwan Yoo, Seongjin Shin, Dongyoon Han, Jinwoo Shin, Kang Min Yoo Permutation-Based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data
Xinshuai Dong, Ignavier Ng, Boyang Sun, Haoyue Dai, Guang-Yuan Hao, Shunxing Fan, Peter Spirtes, Yumou Qiu, Kun Zhang Persistent Topological Features in Large Language Models
Yuri Gardinazzi, Karthik Viswanathan, Giada Panerai, Alessio Ansuini, Alberto Cazzaniga, Matteo Biagetti PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction
Aaron Wenteler, Martina Occhetta, Nikhil Branson, Victor Curean, Magdalena Huebner, William Dee, William Connell, Siu Pui Chung, Alex Hawkins-Hooker, Yasha Ektefaie, César Miguel Valdez Córdova, Amaya Gallagher-Syed PF3plat: Pose-Free Feed-Forward 3D Gaussian Splatting for Novel View Synthesis
Sunghwan Hong, Jaewoo Jung, Heeseong Shin, Jisang Han, Jiaolong Yang, Chong Luo, Seungryong Kim PhantomWiki: On-Demand Datasets for Reasoning and Retrieval Evaluation
Albert Gong, Kamilė Stankevičiūtė, Chao Wan, Anmol Kabra, Raphael Thesmar, Johann Lee, Julius Klenke, Carla P Gomes, Kilian Q Weinberger Physics-Informed Generative Modeling of Wireless Channels
Benedikt Böck, Andreas Oeldemann, Timo Mayer, Francesco Rossetto, Wolfgang Utschick PILAF: Optimal Human Preference Sampling for Reward Modeling
Yunzhen Feng, Ariel Kwiatkowski, Kunhao Zheng, Julia Kempe, Yaqi Duan Piloting Structure-Based Drug Design via Modality-Specific Optimal Schedule
Keyue Qiu, Yuxuan Song, Zhehuan Fan, Peidong Liu, Zhe Zhang, Mingyue Zheng, Hao Zhou, Wei-Ying Ma PINNsAgent: Automated PDE Surrogation with Large Language Models
Qingpo Wuwu, Chonghan Gao, Tianyu Chen, Yihang Huang, Yuekai Zhang, Jianing Wang, Jianxin Li, Haoyi Zhou, Shanghang Zhang Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks
Lutfi Eren Erdogan, Nicholas Lee, Sehoon Kim, Suhong Moon, Hiroki Furuta, Gopala Anumanchipalli, Kurt Keutzer, Amir Gholami PoisonBench: Assessing Language Model Vulnerability to Poisoned Preference Data
Tingchen Fu, Mrinank Sharma, Philip Torr, Shay B Cohen, David Krueger, Fazl Barez Policy Filtration for RLHF to Mitigate Noise in Reward Models
Chuheng Zhang, Wei Shen, Li Zhao, Xuyun Zhang, Xiaolong Xu, Wanchun Dou, Jiang Bian Policy Gradient with Tree Expansion
Gal Dalal, Assaf Hallak, Gugan Thoppe, Shie Mannor, Gal Chechik Policy-Labeled Preference Learning: Is Preference Enough for RLHF?
Taehyun Cho, Seokhun Ju, Seungyub Han, Dohyeong Kim, Kyungjae Lee, Jungwoo Lee Polybasic Speculative Decoding Through a Theoretical Perspective
Ruilin Wang, Huixia Li, Yuexiao Ma, Xiawu Zheng, Fei Chao, Xuefeng Xiao, Rongrong Ji Polynomial Time Learning Augmented Algorithms for NP-Hard Permutation Problems
Evripidis Bampis, Bruno Escoffier, Dimitris Fotakis, Panagiotis Patsilinakos, Michalis Xefteris Position: AI Agents Need Authenticated Delegation
Tobin South, Samuele Marro, Thomas Hardjono, Robert Mahari, Cedric Deslandes Whitney, Alan Chan, Alex Pentland Position: AI Competitions Provide the Gold Standard for Empirical Rigor in GenAI Evaluation
D. Sculley, William Cukierski, Phil Culliton, Sohier Dane, Maggie M Demkin, Ryan Holbrook, Addison Howard, Paul T Mooney, Walter Reade, Meg Risdal, Nate Keating Position: AI Evaluation Should Learn from How We Test Humans
Yan Zhuang, Qi Liu, Zachary Pardos, Patrick C. Kyllonen, Jiyun Zu, Zhenya Huang, Shijin Wang, Enhong Chen Position: AI Safety Should Prioritize the Future of Work
Sanchaita Hazra, Bodhisattwa Prasad Majumder, Tuhin Chakrabarty Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry
Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta, Matthew Trager, Kathlén Kohn Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
Audrey Poinsot, Panayiotis Panayiotou, Alessandro Leite, Nicolas Chesneau, Özgür Şimşek, Marc Schoenauer Position: Certified Robustness Does Not (Yet) Imply Model Security
Andrew Craig Cullen, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein Position: Challenges and Future Directions of Data-Centric AI Alignment
Min-Hsuan Yeh, Jeffrey Wang, Xuefeng Du, Seongheon Park, Leitian Tao, Shawn Im, Yixuan Li Position: Democratic AI Is Possible. the Democracy Levels Framework Shows How It Might Work.
Aviv Ovadya, Kyle Redman, Luke Thorburn, Quan Ze Chen, Oliver Smith, Flynn Devine, Andrew Konya, Smitha Milli, Manon Revel, Kevin Feng, Amy X Zhang, Bilva Chandra, Michiel A. Bakker, Atoosa Kasirzadeh Position: Editing Large Language Models Poses Serious Safety Risks
Paul Youssef, Zhixue Zhao, Daniel Braun, Jörg Schlötterer, Christin Seifert Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alexandra Chouldechova, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nicholas J Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs Position: Formal Mathematical Reasoning—A New Frontier in AI
Kaiyu Yang, Gabriel Poesia, Jingxuan He, Wenda Li, Kristin E. Lauter, Swarat Chaudhuri, Dawn Song Position: Future Research and Challenges Remain Towards AI for Software Engineering
Alex Gu, Naman Jain, Wen-Ding Li, Manish Shetty, Kevin Ellis, Koushik Sen, Armando Solar-Lezama Position: General Intelligence Requires Reward-Based Pretraining
Seungwook Han, Jyothish Pari, Samuel J. Gershman, Pulkit Agrawal Position: Graph Learning Will Lose Relevance Due to Poor Benchmarks
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris Position: Graph Matching Systems Deserve Better Benchmarks
Indradyumna Roy, Saswat Meher, Eeshaan Jain, Soumen Chakrabarti, Abir De Position: Human Baselines in Model Evaluations Need Rigor and Transparency (With Recommendations & Reporting Checklist)
Kevin Wei, Patricia Paskov, Sunishchal Dev, Michael J Byun, Anka Reuel, Xavier Roberts-Gaal, Rachel Calcott, Evie Coxon, Chinmay Deshpande Position: Humanity Faces Existential Risk from Gradual Disempowerment
Jan Kulveit, Raymond Douglas, Nora Ammann, Deger Turan, David Krueger, David Duvenaud Position: In-House Evaluation Is Not Enough. Towards Robust Third-Party Evaluation and Flaw Disclosure for General-Purpose AI
Shayne Longpre, Kevin Klyman, Ruth Elisabeth Appel, Sayash Kapoor, Rishi Bommasani, Michelle Sahar, Sean Mcgregor, Avijit Ghosh, Borhane Blili-Hamelin, Nathan Butters, Alondra Nelson, Dr. Amit Elazari, Andrew Sellars, Casey John Ellis, Dane Sherrets, Dawn Song, Harley Geiger, Ilona Cohen, Lauren Mcilvenny, Madhulika Srikumar, Mark M. Jaycox, Markus Anderljung, Nadine Farid Johnson, Nicholas Carlini, Nicolas Miailhe, Nik Marda, Peter Henderson, Rebecca S. Portnoff, Rebecca Weiss, Victoria Westerhoff, Yacine Jernite, Rumman Chowdhury, Percy Liang, Arvind Narayanan Position: It Is Time We Test Neural Computation in Vitro
Frithjof Gressmann, Ashley Chen, Lily Hexuan Xie, Nancy Amato, Lawrence Rauchwerger Position: Language Model Developers Should Report Train-Test Overlap
Andy K Zhang, Kevin Klyman, Yifan Mai, Yoav Levine, Yian Zhang, Rishi Bommasani, Percy Liang Position: Lifetime Tuning Is Incompatible with Continual Reinforcement Learning
Golnaz Mesbahi, Parham Mohammad Panahi, Olya Mastikhina, Steven Tang, Martha White, Adam White Position: LLM Social Simulations Are a Promising Research Method
Jacy Reese Anthis, Ryan Liu, Sean M Richardson, Austin C. Kozlowski, Bernard Koch, Erik Brynjolfsson, James Evans, Michael S. Bernstein Position: Machine Learning Models Have a Supply Chain Problem
Sarah Meiklejohn, Hayden Blauzvern, Mihai Maruseac, Spencer Schrock, Laurent Simon, Ilia Shumailov Position: Medical Large Language Model Benchmarks Should Prioritize Construct Validity
Ahmed Alaa, Thomas Hartvigsen, Niloufar Golchini, Shiladitya Dutta, Frances Dean, Inioluwa Deborah Raji, Travis Zack Position: Political Neutrality in AI Is Impossible — But Here Is How to Approximate It
Jillian Fisher, Ruth Elisabeth Appel, Chan Young Park, Yujin Potter, Liwei Jiang, Taylor Sorensen, Shangbin Feng, Yulia Tsvetkov, Margaret Roberts, Jennifer Pan, Dawn Song, Yejin Choi Position: Principles of Animal Cognition to Improve LLM Evaluations
Sunayana Rane, Cyrus F. Kirkman, Graham Todd, Amanda Royka, Ryan M.C. Law, Erica Cartmill, Jacob Gates Foster Position: Retrieval-Augmented Systems Can Be Dangerous Medical Communicators
Lionel Wong, Ayman Ali, Raymond M Xiong, Zejiang Shen, Yoon Kim, Monica Agrawal Position: Solve Layerwise Linear Models First to Understand Neural Dynamical Phenomena (Neural Collapse, Emergence, Lazy/Rich Regime, and Grokking)
Yoonsoo Nam, Seok Hyeong Lee, Clémentine Carla Juliette Dominé, Yeachan Park, Charles London, Wonyl Choi, Niclas Alexander Göring, Seungjai Lee Position: Stop Treating ‘AGI’ as the North-Star Goal of AI Research
Borhane Blili-Hamelin, Christopher Graziul, Leif Hancox-Li, Hananel Hazan, El-Mahdi El-Mhamdi, Avijit Ghosh, Katherine A Heller, Jacob Metcalf, Fabricio Murai, Eryk Salvaggio, Andrew J Smart, Todd Snider, Mariame Tighanimine, Talia Ringer, Margaret Mitchell, Shiri Dori-Hacohen Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection
Yucen Lily Li, Daohan Lu, Polina Kirichenko, Shikai Qiu, Tim G. J. Rudner, C. Bayan Bruss, Andrew Gordon Wilson Position: The Future of Bayesian Prediction Is Prior-Fitted
Samuel Müller, Arik Reuter, Noah Hollmann, David Rügamer, Frank Hutter Position: The Right to AI
Rashid Mushkani, Hugo Berard, Allison Cohen, Shin Koseki Position: Theory of Mind Benchmarks Are Broken for Large Language Models
Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das, Miao Liu, Justin D. Weisz, Murray Campbell Position: Trustworthy AI Agents Require the Integration of Large Language Models and Formal Methods
Yedi Zhang, Yufan Cai, Xinyue Zuo, Xiaokun Luan, Kailong Wang, Zhe Hou, Yifan Zhang, Zhiyuan Wei, Meng Sun, Jun Sun, Jing Sun, Jin Song Dong Position: We Need an Algorithmic Understanding of Generative AI
Oliver Eberle, Thomas Austin Mcgee, Hamza Giaffar, Taylor Whittington Webb, Ida Momennejad Position: When Incentives Backfire, Data Stops Being Human
Sebastin Santy, Prasanta Bhattacharya, Manoel Horta Ribeiro, Kelsey R Allen, Sewoong Oh Position: You Can’t Manufacture a NeRF
Ma Kimmel, Mueed Ur Rehman, Yonatan Bisk, Gary K. Fedder Positional Attention: Expressivity and Learnability of Algorithmic Computation
Artur Back De Luca, George Giapitzakis, Shenghao Yang, Petar Veličković, Kimon Fountoulakis Positive-Unlabeled AUC Maximization Under Covariate Shift
Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Kazuki Adachi, Yasuhiro Fujiwara Potemkin Understanding in Large Language Models
Marina Mancoridis, Bec Weeks, Keyon Vafa, Sendhil Mullainathan Pre-Training Auto-Regressive Robotic Models with 4D Representations
Dantong Niu, Yuvan Sharma, Haoru Xue, Giscard Biamby, Junyi Zhang, Ziteng Ji, Trevor Darrell, Roei Herzig Predicting High-Precision Depth on Low-Precision Devices Using 2D Hilbert Curves
Mykhail Uss, Ruslan Yermolenko, Oleksii Shashko, Olena Kolodiazhna, Ivan Safonov, Volodymyr Savin, Yoonjae Yeo, Seowon Ji, Jaeyun Jeong Predicting Mutational Effects on Protein Binding from Folding Energy
Arthur Deng, Karsten D. Householder, Fang Wu, K. Christopher Garcia, Brian L. Trippe Prediction Models That Learn to Avoid Missing Values
Lena Stempfle, Anton Matsson, Newton Mwai, Fredrik D. Johansson Prediction via Shapley Value Regression
Amr Alkhatib, Roman Bresson, Henrik Boström, Michalis Vazirgiannis Prediction-Aware Learning in Multi-Agent Systems
Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael I. Jordan, Alain Oliviero Durmus Prediction-Powered E-Values
Daniel Csillag, Claudio Jose Struchiner, Guilherme Tegoni Goedert Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Kashun Shum, Yuzhen Huang, Hongjian Zou, Qi Ding, Yixuan Liao, Xiaoxin Chen, Qian Liu, Junxian He Preference Adaptive and Sequential Text-to-Image Generation
Ofir Nabati, Guy Tennenholtz, Chihwei Hsu, Moonkyung Ryu, Deepak Ramachandran, Yinlam Chow, Xiang Li, Craig Boutilier Preference Optimization for Combinatorial Optimization Problems
Mingjun Pan, Guanquan Lin, You-Wei Luo, Bin Zhu, Zhien Dai, Lijun Sun, Chun Yuan Preserving AUC Fairness in Learning with Noisy Protected Groups
Mingyang Wu, Li Lin, Wenbin Zhang, Xin Wang, Zhenhuan Yang, Shu Hu PRIME: Deep Imbalanced Regression with Proxies
Jongin Lim, Sucheol Lee, Daeho Um, Sung-Un Park, Jinwoo Shin Primitive Vision: Improving Diagram Understanding in MLLMs
Shan Zhang, Aotian Chen, Yanpeng Sun, Jindong Gu, Yi-Yu Zheng, Piotr Koniusz, Kai Zou, Anton Van Den Hengel, Yuan Xue Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting
Jan Schuchardt, Mina Dalirrooyfard, Jed Guzelkabaagac, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann Privacy Attacks on Image AutoRegressive Models
Antoni Kowalczuk, Jan Dubiński, Franziska Boenisch, Adam Dziedzic Private Lossless Multiple Release
Joel Daniel Andersson, Lukas Retschmeier, Boel Nelson, Rasmus Pagh Private Model Personalization Revisited
Conor Snedeker, Xinyu Zhou, Raef Bassily Proactive Agents for Multi-Turn Text-to-Image Generation Under Uncertainty
Meera Hahn, Wenjun Zeng, Nithish Kannen, Rich Galt, Kartikeya Badola, Been Kim, Zi Wang Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes
Jie Liu, Pan Zhou, Zehao Xiao, Jiayi Shen, Wenzhe Yin, Jan-Jakob Sonke, Efstratios Gavves Probably Approximately Global Robustness Certification
Peter Blohm, Patrick Indri, Thomas Gärtner, Sagar Malhotra Probing Visual Language Priors in VLMs
Tiange Luo, Ang Cao, Gunhee Lee, Justin Johnson, Honglak Lee Procurement Auctions via Approximately Optimal Submodular Optimization
Yuan Deng, Amin Karbasi, Vahab Mirrokni, Renato Paes Leme, Grigoris Velegkas, Song Zuo ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation
Tianci Bu, Le Zhou, Wenchuan Yang, Jianhong Mou, Kang Yang, Suoyi Tan, Feng Yao, Jingyuan Wang, Xin Lu Progressive Tempering Sampler with Diffusion
Severi Rissanen, Ruikang Ouyang, Jiajun He, Wenlin Chen, Markus Heinonen, Arno Solin, José Miguel Hernández-Lobato Projection Pursuit Density Ratio Estimation
Meilin Wang, Wei Huang, Mingming Gong, Zheng Zhang Prompt-to-Leaderboard: Prompt-Adaptive LLM Evaluations
Evan Frick, Connor Chen, Joseph Tennyson, Tianle Li, Wei-Lin Chiang, Anastasios Nikolas Angelopoulos, Ion Stoica Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery for Foundation Model Internet Agents
Yifei Zhou, Qianlan Yang, Kaixiang Lin, Min Bai, Xiong Zhou, Yu-Xiong Wang, Sergey Levine, Li Erran Li ProSec: Fortifying Code LLMs with Proactive Security Alignment
Xiangzhe Xu, Zian Su, Jinyao Guo, Kaiyuan Zhang, Zhenting Wang, Xiangyu Zhang Protein Structure Tokenization: Benchmarking and New Recipe
Xinyu Yuan, Zichen Wang, Marcus D. Collins, Huzefa Rangwala Protriever: End-to-End Differentiable Protein Homology Search for Fitness Prediction
Ruben Weitzman, Peter Mørch Groth, Lood Van Niekerk, Aoi Otani, Yarin Gal, Debora Susan Marks, Pascal Notin Provable In-Context Vector Arithmetic via Retrieving Task Concepts
Dake Bu, Wei Huang, Andi Han, Atsushi Nitanda, Qingfu Zhang, Hau-San Wong, Taiji Suzuki Provable Length Generalization in Sequence Prediction via Spectral Filtering
Annie Marsden, Evan Dogariu, Naman Agarwal, Xinyi Chen, Daniel Suo, Elad Hazan Provable Maximum Entropy Manifold Exploration via Diffusion Models
Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause Provably Improving Generalization of Few-Shot Models with Synthetic Data
Lan-Cuong Nguyen, Quan Nguyen-Tri, Bang Tran Khanh, Dung D. Le, Long Tran-Thanh, Khoat Than Proxsparse: Regularized Learning of Semi-Structured Sparsity Masks for Pretrained LLMs
Hongyi Liu, Rajarshi Saha, Zhen Jia, Youngsuk Park, Jiaji Huang, Shoham Sabach, Yu-Xiang Wang, George Karypis Proxy-FDA: Proxy-Based Feature Distribution Alignment for Fine-Tuning Vision Foundation Models Without Forgetting
Chen Huang, Skyler Seto, Hadi Pouransari, Mehrdad Farajtabar, Raviteja Vemulapalli, Fartash Faghri, Oncel Tuzel, Barry-John Theobald, Joshua M. Susskind Prune ’n Predict: Optimizing LLM Decision-Making with Conformal Prediction
Harit Vishwakarma, Alan Mishler, Thomas Cook, Niccolo Dalmasso, Natraj Raman, Sumitra Ganesh Pruning for GNNs: Lower Complexity with Comparable Expressiveness
Dun Ma, Jianguo Chen, Wenguo Yang, Suixiang Gao, Shengminjie Chen Putnam-AXIOM: A Functional & Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs
Aryan Gulati, Brando Miranda, Eric Chen, Emily Xia, Kai Fronsdal, Bruno De Moraes Dumont, Sanmi Koyejo Puzzle: Distillation-Based NAS for Inference-Optimized LLMs
Akhiad Bercovich, Tomer Ronen, Talor Abramovich, Nir Ailon, Nave Assaf, Mohammed Dabbah, Ido Galil, Amnon Geifman, Yonatan Geifman, Izhak Golan, Netanel Haber, Ehud Dov Karpas, Roi Koren, Itay Levy, Pavlo Molchanov, Shahar Mor, Zach Moshe, Najeeb Nabwani, Omri Puny, Ran Rubin, Itamar Schen, Ido Shahaf, Oren Tropp, Omer Ullman Argov, Ran Zilberstein, Ran El-Yaniv Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers
Weilun Feng, Chuanguang Yang, Haotong Qin, Xiangqi Li, Yu Wang, Zhulin An, Libo Huang, Boyu Diao, Zixiang Zhao, Yongjun Xu, Michele Magno QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
Zongyu Lin, Yao Tang, Xingcheng Yao, Da Yin, Ziniu Hu, Yizhou Sun, Kai-Wei Chang Quamba2: A Robust and Scalable Post-Training Quantization Framework for Selective State Space Models
Hung-Yueh Chiang, Chi-Chih Chang, Natalia Frumkin, Kai-Chiang Wu, Mohamed S. Abdelfattah, Diana Marculescu Quantifying Memory Utilization with Effective State-Size
Rom Parnichkun, Neehal Tumma, Armin W Thomas, Alessandro Moro, Qi An, Taiji Suzuki, Atsushi Yamashita, Michael Poli, Stefano Massaroli Quantifying Prediction Consistency Under Fine-Tuning Multiplicity in Tabular LLMs
Faisal Hamman, Pasan Dissanayake, Saumitra Mishra, Freddy Lecue, Sanghamitra Dutta QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache
Rishabh Tiwari, Haocheng Xi, Aditya Tomar, Coleman Richard Charles Hooper, Sehoon Kim, Maxwell Horton, Mahyar Najibi, Michael W. Mahoney, Kurt Keutzer, Amir Gholami Quantum Algorithms for Finite-Horizon Markov Decision Processes
Bin Luo, Yuwen Huang, Jonathan Allcock, Xiaojun Lin, Shengyu Zhang, John C.S. Lui Quantum Speedup for Hypergraph Sparsification
Chenghua Liu, Minbo Gao, Zhengfeng Ji, Mingsheng Ying QuEST: Stable Training of LLMs with 1-Bit Weights and Activations
Andrei Panferov, Jiale Chen, Soroush Tabesh, Mahdi Nikdan, Dan Alistarh R.I.P.: Better Models by Survival of the Fittest Prompts
Ping Yu, Weizhe Yuan, Olga Golovneva, Tianhao Wu, Sainbayar Sukhbaatar, Jason E Weston, Jing Xu R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-Agent Reinforcement Learning
Harsh Goel, Mohammad Omama, Behdad Chalaki, Vaishnav Tadiparthi, Ehsan Moradi Pari, Sandeep P. Chinchali Random Feature Representation Boosting
Nikita Zozoulenko, Thomas Cass, Lukas Gonon Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures
Jie Gao, Rajesh Jayaram, Benedikt Kolbe, Shay Sapir, Chris Schwiegelshohn, Sandeep Silwal, Erik Waingarten Rank-One Modified Value Iteration
Arman Sharifi Kolarijani, Tolga Ok, Peyman Mohajerin Esfahani, Mohamad Amin Sharifi Kolarijani Ranked from Within: Ranking Large Multimodal Models Without Labels
Weijie Tu, Weijian Deng, Dylan Campbell, Yu Yao, Jiyang Zheng, Tom Gedeon, Tongliang Liu RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals
David Reber, Sean M Richardson, Todd Nief, Cristina Garbacea, Victor Veitch RBench: Graduate-Level Multi-Disciplinary Benchmarks for LLM & MLLM Complex Reasoning Evaluation
Meng-Hao Guo, Jiajun Xu, Yi Zhang, Jiaxi Song, Haoyang Peng, Yi-Xuan Deng, Xinzhi Dong, Kiyohiro Nakayama, Zhengyang Geng, Chen Wang, Bolin Ni, Guo-Wei Yang, Yongming Rao, Houwen Peng, Han Hu, Gordon Wetzstein, Shi-Min Hu RE-Bench: Evaluating Frontier AI R&D Capabilities of Language Model Agents Against Human Experts
Hjalmar Wijk, Tao Roa Lin, Joel Becker, Sami Jawhar, Neev Parikh, Thomas Broadley, Lawrence Chan, Michael Chen, Joshua M Clymer, Jai Dhyani, Elena Ericheva, Katharyn Garcia, Brian Goodrich, Nikola Jurkovic, Megan Kinniment, Aron Lajko, Seraphina Nix, Lucas Jun Koba Sato, William Saunders, Maksym Taran, Ben West, Elizabeth Barnes RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation
Xinnuo Xu, Rachel Lawrence, Kshitij Dubey, Atharva Pandey, Risa Ueno, Fabian Falck, Aditya V. Nori, Rahul Sharma, Amit Sharma, Javier Gonzalez Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation
Zhuohao Yu, Weizheng Gu, Yidong Wang, Xingru Jiang, Zhengran Zeng, Jindong Wang, Wei Ye, Shikun Zhang Rectifying Conformity Scores for Better Conditional Coverage
Vincent Plassier, Alexander Fishkov, Victor Dheur, Mohsen Guizani, Souhaib Ben Taieb, Maxim Panov, Eric Moulines Reducing Tool Hallucination via Reliability Alignment
Hongshen Xu, Zichen Zhu, Lei Pan, Zihan Wang, Su Zhu, Da Ma, Ruisheng Cao, Lu Chen, Kai Yu ReferSplat: Referring Segmentation in 3D Gaussian Splatting
Shuting He, Guangquan Jie, Changshuo Wang, Yun Zhou, Shuming Hu, Guanbin Li, Henghui Ding Reflection-Bench: Evaluating Epistemic Agency in Large Language Models
Lingyu Li, Yixu Wang, Haiquan Zhao, Shuqi Kong, Yan Teng, Chunbo Li, Yingchun Wang Reflection-Window Decoding: Text Generation with Selective Refinement
Zeyu Tang, Zhenhao Chen, Xiangchen Song, Loka Li, Yunlong Deng, Yifan Shen, Guangyi Chen, Peter Spirtes, Kun Zhang ReFocus: Visual Editing as a Chain of Thought for Structured Image Understanding
Xingyu Fu, Minqian Liu, Zhengyuan Yang, John Richard Corring, Yijuan Lu, Jianwei Yang, Dan Roth, Dinei Florencio, Cha Zhang REG: Rectified Gradient Guidance for Conditional Diffusion Models
Zhengqi Gao, Kaiwen Zha, Tianyuan Zhang, Zihui Xue, Duane S Boning Regress, Don’t Guess: A Regression-like Loss on Number Tokens for Language Models
Jonas Zausinger, Lars Pennig, Anamarija Kozina, Sean Sdahl, Julian Sikora, Adrian Dendorfer, Timofey Kuznetsov, Mohamad Hagog, Nina Wiedemann, Kacper Chlodny, Vincent Limbach, Anna Ketteler, Thorben Prein, Vishwa Mohan Singh, Michael Danziger, Jannis Born Reidentify: Context-Aware Identity Generation for Contextual Multi-Agent Reinforcement Learning
Zhiwei Xu, Kun Hu, Xin Xin, Weiliang Meng, Yiwei Shi, Hangyu Mao, Bin Zhang, Dapeng Li, Jiangjin Yin ReinboT: Amplifying Robot Visual-Language Manipulation with Reinforcement Learning
Hongyin Zhang, Zifeng Zhuang, Han Zhao, Pengxiang Ding, Hongchao Lu, Donglin Wang REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective
Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Vincent Cohen-Addad, Johannes Gasteiger, Stephan Günnemann Reinforced Lifelong Editing for Language Models
Zherui Li, Houcheng Jiang, Hao Chen, Baolong Bi, Zhenhong Zhou, Fei Sun, Junfeng Fang, Xiang Wang Reinforcement Learning with Random Time Horizons
Enric Ribera Borrell, Lorenz Richter, Christof Schuette Reinforcement Learning with Segment Feedback
Yihan Du, Anna Winnicki, Gal Dalal, Shie Mannor, R. Srikant Rejecting Hallucinated State Targets During Planning
Harry Zhao, Tristan Sylvain, Romain Laroche, Doina Precup, Yoshua Bengio Relational Conformal Prediction for Correlated Time Series
Andrea Cini, Alexander Jenkins, Danilo Mandic, Cesare Alippi, Filippo Maria Bianchi Relative Error Fair Clustering in the Weak-Strong Oracle Model
Vladimir Braverman, Prathamesh Dharangutte, Shaofeng H.-C. Jiang, Hoai-An Nguyen, Chen Wang, Yubo Zhang, Samson Zhou Reliable and Efficient Amortized Model-Based Evaluation
Sang T. Truong, Yuheng Tu, Percy Liang, Bo Li, Sanmi Koyejo Rényi Neural Processes
Xuesong Wang, He Zhao, Edwin V. Bonilla Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing
Kento Nishi, Rahul Ramesh, Maya Okawa, Mikail Khona, Hidenori Tanaka, Ekdeep Singh Lubana Representation Surgery in Model Merging with Probabilistic Modeling
Qi Wei, Shuo He, Enneng Yang, Tingcong Liu, Haobo Wang, Lei Feng, Bo An Representative Language Generation
Charlotte Peale, Vinod Raman, Omer Reingold Representative Ranking for Deliberation in the Public Sphere
Manon Revel, Smitha Milli, Tyler Lu, Jamelle Watson-Daniels, Maximilian Nickel ResearchTown: Simulator of Human Research Community
Haofei Yu, Zhaochen Hong, Zirui Cheng, Kunlun Zhu, Keyang Xuan, Jinwei Yao, Tao Feng, Jiaxuan You Resolving Lexical Bias in Model Editing
Hammad Rizwan, Domenic Rosati, Ga Wu, Hassan Sajjad RestoreGrad: Signal Restoration Using Conditional Denoising Diffusion Models with Jointly Learned Prior
Ching-Hua Lee, Chouchang Yang, Jaejin Cho, Yashas Malur Saidutta, Rakshith Sharma Srinivasa, Yilin Shen, Hongxia Jin Rethink GraphODE Generalization Within Coupled Dynamical System
Guancheng Wan, Zijie Huang, Wanjia Zhao, Xiao Luo, Yizhou Sun, Wei Wang Rethinking Aleatoric and Epistemic Uncertainty
Freddie Bickford Smith, Jannik Kossen, Eleanor Trollope, Mark Van Der Wilk, Adam Foster, Tom Rainforth Rethinking Causal Ranking: A Balanced Perspective on Uplift Model Evaluation
Minqin Zhu, Zexu Sun, Ruoxuan Xiong, Anpeng Wu, Baohong Li, Caizhi Tang, Jun Zhou, Fei Wu, Kun Kuang Rethinking Chain-of-Thought from the Perspective of Self-Training
Zongqian Wu, Baoduo Xu, Ruochen Cui, Mengmeng Zhan, Xiaofeng Zhu, Lei Feng Rethinking Confidence Scores and Thresholds in Pseudolabeling-Based SSL
Harit Vishwakarma, Yi Chen, Satya Sai Srinath Namburi Gnvv, Sui Jiet Tay, Ramya Korlakai Vinayak, Frederic Sala Rethinking Time Encoding via Learnable Transformation Functions
Xi Chen, Yateng Tang, Jiarong Xu, Jiawei Zhang, Siwei Zhang, Sijia Peng, Xuehao Zheng, Yun Xiong Retraining with Predicted Hard Labels Provably Increases Model Accuracy
Rudrajit Das, Inderjit S Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong Retraining-Free Merging of Sparse MoE via Hierarchical Clustering
I-Chun Chen, Hsu-Shen Liu, Wei-Fang Sun, Chen-Hao Chao, Yen-Chang Hsu, Chun-Yi Lee Retrieval Augmented Time Series Forecasting
Sungwon Han, Seungeon Lee, Meeyoung Cha, Sercan O Arik, Jinsung Yoon Retrieval Augmented Zero-Shot Enzyme Generation for Specified Substrate
Jiahe Du, Kaixiong Zhou, Xinyu Hong, Zhaozhuo Xu, Jinbo Xu, Xiao Huang Retrieval-Augmented Language Model for Knowledge-Aware Protein Encoding
Jiasheng Zhang, Delvin Ce Zhang, Shuang Liang, Zhengpin Li, Zhitao Ying, Jie Shao Retrieval-Augmented Perception: High-Resolution Image Perception Meets Visual RAG
Wenbin Wang, Yongcheng Jing, Liang Ding, Yingjie Wang, Li Shen, Yong Luo, Bo Du, Dacheng Tao ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks
Yufei Guo, Yuhan Zhang, Zhou Jie, Xiaode Liu, Xin Tong, Yuanpei Chen, Weihang Peng, Zhe Ma Revisiting Non-Acyclic GFlowNets in Discrete Environments
Nikita Morozov, Ian Maksimov, Daniil Tiapkin, Sergey Samsonov Revolve: Optimizing AI Systems by Tracking Response Evolution in Textual Optimization
Peiyan Zhang, Haibo Jin, Leyang Hu, Xinnuo Li, Liying Kang, Man Luo, Yangqiu Song, Haohan Wang Reward Translation via Reward Machine in Semi-Alignable MDPs
Yun Hua, Haosheng Chen, Wenhao Li, Bo Jin, Baoxiang Wang, Hongyuan Zha, Xiangfeng Wang Reward-Augmented Data Enhances Direct Preference Alignment of LLMs
Shenao Zhang, Zhihan Liu, Boyi Liu, Yufeng Zhang, Yingxiang Yang, Yongfei Liu, Liyu Chen, Tao Sun, Zhaoran Wang Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs
Ziyu Ye, Rishabh Agarwal, Tianqi Liu, Rishabh Joshi, Sarmishta Velury, Quoc V Le, Qijun Tan, Yuan Liu Reward-Guided Speculative Decoding for Efficient LLM Reasoning
Baohao Liao, Yuhui Xu, Hanze Dong, Junnan Li, Christof Monz, Silvio Savarese, Doyen Sahoo, Caiming Xiong RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning
Jonas Gehring, Kunhao Zheng, Jade Copet, Vegard Mella, Taco Cohen, Gabriel Synnaeve RLTHF: Targeted Human Feedback for LLM Alignment
Yifei Xu, Tusher Chakraborty, Emre Kiciman, Bibek Aryal, Srinagesh Sharma, Songwu Lu, Ranveer Chandra Robust and Conjugate Spatio-Temporal Gaussian Processes
William Laplante, Matias Altamirano, Andrew B. Duncan, Jeremias Knoblauch, Francois-Xavier Briol Robust Automatic Modulation Classification with Fuzzy Regularization
Xinyan Liang, Ruijie Sang, Yuhua Qian, Qian Guo, Feijiang Li, Liang Du Robust Autonomy Emerges from Self-Play
Marco Cusumano-Towner, David Hafner, Alexander Hertzberg, Brody Huval, Aleksei Petrenko, Eugene Vinitsky, Erik Wijmans, Taylor W. Killian, Stuart Bowers, Ozan Sener, Philipp Kraehenbuehl, Vladlen Koltun Robust ML Auditing Using Prior Knowledge
Jade Garcia Bourrée, Augustin Godinot, Sayan Biswas, Anne-Marie Kermarrec, Erwan Le Merrer, Gilles Tredan, Martijn De Vos, Milos Vujasinovic Robust Sparsification via Sensitivity
Chansophea Wathanak In, Yi Li, David Woodruff, Xuan Wu Robust Spatio-Temporal Centralized Interaction for OOD Learning
Jiaming Ma, Binwu Wang, Pengkun Wang, Zhengyang Zhou, Xu Wang, Yang Wang RobustLight: Improving Robustness via Diffusion Reinforcement Learning for Traffic Signal Control
Mingyuan Li, Jiahao Wang, Guangsheng Yu, Xu Wang, Qianrun Chen, Wei Ni, Lixiang Li, Haipeng Peng RobustZero: Enhancing MuZero Reinforcement Learning Robustness to State Perturbations
Yushuai Li, Hengyu Liu, Torben Bach Pedersen, Yuqiang He, Kim Guldstrand Larsen, Lu Chen, Christian S. Jensen, Jiachen Xu, Tianyi Li RollingQ: Reviving the Cooperation Dynamics in Multimodal Transformer
Haotian Ni, Yake Wei, Hang Liu, Gong Chen, Chong Peng, Hao Lin, Di Hu ROME Is Forged in Adversity: Robust Distilled Datasets via Information Bottleneck
Zheng Zhou, Wenquan Feng, Qiaosheng Zhang, Shuchang Lyu, Qi Zhao, Guangliang Cheng ROPO: Robust Preference Optimization for Large Language Models
Xize Liang, Chao Chen, Shuang Qiu, Jie Wang, Yue Wu, Zhihang Fu, Hanzhu Chen, Feng Wu, Jieping Ye rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Xinyu Guan, Li Lyna Zhang, Yifei Liu, Ning Shang, Youran Sun, Yi Zhu, Fan Yang, Mao Yang RUN: Reversible Unfolding Network for Concealed Object Segmentation
Chunming He, Rihan Zhang, Fengyang Xiao, Chengyu Fang, Longxiang Tang, Yulun Zhang, Linghe Kong, Deng-Ping Fan, Kai Li, Sina Farsiu RWKVQuant: Quantizing the RWKV Family with Proxy Guided Hybrid of Scalar and Vector Quantization
Chen Xu, Yuxuan Yue, Zukang Xu, Xing Hu, Jiangyong Yu, Zhixuan Chen, Sifan Zhou, Zhihang Yuan, Dawei Yang S2-Track: A Simple yet Strong Approach for End-to-End 3D Multi-Object Tracking
Tao Tang, Lijun Zhou, Pengkun Hao, Zihang He, Kalok Ho, Shuo Gu, Zhihui Hao, Haiyang Sun, Kun Zhan, Peng Jia, Xianpeng Lang, Xiaodan Liang S4S: Solving for a Fast Diffusion Model Solver
Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh Sable: A Performant, Efficient and Scalable Sequence Model for MARL
Omayma Mahjoub, Sasha Abramowitz, Ruan John De Kock, Wiem Khlifi, Simon Verster Du Toit, Jemma Daniel, Louay Ben Nessir, Louise Beyers, Juan Claude Formanek, Liam Clark, Arnu Pretorius SADA: Stability-Guided Adaptive Diffusion Acceleration
Ting Jiang, Yixiao Wang, Hancheng Ye, Zishan Shao, Jingwei Sun, Jingyang Zhang, Zekai Chen, Jianyi Zhang, Yiran Chen, Hai Li SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability
Adam Karvonen, Can Rager, Johnny Lin, Curt Tigges, Joseph Isaac Bloom, David Chanin, Yeu-Tong Lau, Eoin Farrell, Callum Stuart Mcdougall, Kola Ayonrinde, Demian Till, Matthew Wearden, Arthur Conmy, Samuel Marks, Neel Nanda Safe Delta: Consistently Preserving Safety When Fine-Tuning LLMs on Diverse Datasets
Ning Lu, Shengcai Liu, Jiahao Wu, Weiyu Chen, Zhirui Zhang, Yew-Soon Ong, Qi Wang, Ke Tang SafeArena: Evaluating the Safety of Autonomous Web Agents
Ada Defne Tur, Nicholas Meade, Xing Han Lù, Alejandra Zambrano, Arkil Patel, Esin Durmus, Spandana Gella, Karolina Stanczak, Siva Reddy SafeMap: Robust HD mAP Construction from Incomplete Observations
Xiaoshuai Hao, Lingdong Kong, Rong Yin, Pengwei Wang, Jing Zhang, Yunfeng Diao, Shu Zhao Safety Reasoning with Guidelines
Haoyu Wang, Zeyu Qin, Li Shen, Xueqian Wang, Dacheng Tao, Minhao Cheng Safety-Polarized and Prioritized Reinforcement Learning
Ke Fan, Jinpeng Zhang, Xuefeng Zhang, Yunze Wu, Jingyu Cao, Yuan Zhou, Jianzhu Ma SafetyAnalyst: Interpretable, Transparent, and Steerable Safety Moderation for AI Behavior
Jing-Jing Li, Valentina Pyatkin, Max Kleiman-Weiner, Liwei Jiang, Nouha Dziri, Anne Collins, Jana Schaich Borg, Maarten Sap, Yejin Choi, Sydney Levine SAM2Act: Integrating Visual Foundation Model with a Memory Architecture for Robotic Manipulation
Haoquan Fang, Markus Grotz, Wilbert Pumacay, Yi Ru Wang, Dieter Fox, Ranjay Krishna, Jiafei Duan Sample Efficient Demonstration Selection for In-Context Learning
Kiran Purohit, Venktesh V, Sourangshu Bhattacharya, Avishek Anand SAN: Hypothesizing Long-Term Synaptic Development and Neural Engram Mechanism in Scalable Model’s Parameter-Efficient Fine-Tuning
Gaole Dai, Chun-Kai Fan, Yiming Tang, Zhi Zhang, Yuan Zhang, Yulu Gan, Qizhe Zhang, Cheng-Ching Tseng, Shanghang Zhang, Tiejun Huang SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer
Enze Xie, Junsong Chen, Yuyang Zhao, Jincheng Yu, Ligeng Zhu, Yujun Lin, Zhekai Zhang, Muyang Li, Junyu Chen, Han Cai, Bingchen Liu, Daquan Zhou, Song Han SAND: One-Shot Feature Selection with Additive Noise Distortion
Pedram Pad, Hadi Hammoud, Mohamad Dia, Nadim Maamari, Liza Andrea Dunbar Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search
Maohao Shen, Guangtao Zeng, Zhenting Qi, Zhang-Wei Hong, Zhenfang Chen, Wei Lu, Gregory W. Wornell, Subhro Das, David Daniel Cox, Chuang Gan Scaffold with Stochastic Gradients: New Analysis with Linear Speed-up
Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Eric Moulines Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation
Yaowen Hu, Wenxuan Tu, Yue Liu, Xinhang Wan, Junyi Yan, Taichun Zhou, Xinwang Liu Scalable Equilibrium Sampling with Sequential Boltzmann Generators
Charlie B. Tan, Joey Bose, Chen Lin, Leon Klein, Michael M. Bronstein, Alexander Tong Scalable Gaussian Processes with Latent Kronecker Structure
Jihao Andreas Lin, Sebastian Ament, Maximilian Balandat, David Eriksson, José Miguel Hernández-Lobato, Eytan Bakshy Scalable Meta-Learning via Mixed-Mode Differentiation
Iurii Kemaev, Dan A. Calian, Luisa M Zintgraf, Gregory Farquhar, Hado Van Hasselt Scalable Private Partition Selection via Adaptive Weighting
Justin Y. Chen, Vincent Cohen-Addad, Alessandro Epasto, Morteza Zadimoghaddam Scaling Inference-Efficient Language Models
Song Bian, Minghao Yan, Shivaram Venkataraman Scaling Large Motion Models with Million-Level Human Motions
Ye Wang, Sipeng Zheng, Bin Cao, Qianshan Wei, Weishuai Zeng, Qin Jin, Zongqing Lu Scaling Laws for Differentially Private Language Models
Ryan Mckenna, Yangsibo Huang, Amer Sinha, Borja Balle, Zachary Charles, Christopher A. Choquette-Choo, Badih Ghazi, Georgios Kaissis, Ravi Kumar, Ruibo Liu, Da Yu, Chiyuan Zhang Scaling Laws for Floating–Point Quantization Training
Xingwu Sun, Shuaipeng Li, Ruobing Xie, Weidong Han, Kan Wu, Zhen Yang, Yixing Li, An Wang, Shuai Li, Jinbao Xue, Yu Cheng, Yangyu Tao, Zhanhui Kang, Cheng-Zhong Xu, Di Wang, Jie Jiang Scaling Laws for Forgetting During Finetuning with Pretraining Data Injection
Louis Béthune, David Grangier, Dan Busbridge, Eleonora Gualdoni, Marco Cuturi, Pierre Ablin Scaling Laws for Pre-Training Agents and World Models
Tim Pearce, Tabish Rashid, David Bignell, Raluca Georgescu, Sam Devlin, Katja Hofmann Scaling Probabilistic Circuits via Monarch Matrices
Honghua Zhang, Meihua Dang, Benjie Wang, Stefano Ermon, Nanyun Peng, Guy Van Den Broeck Scaling Trends in Language Model Robustness
Nikolaus H. R. Howe, Ian R. Mckenzie, Oskar John Hollinsworth, Michał Zając, Tom Tseng, Aaron David Tucker, Pierre-Luc Bacon, Adam Gleave Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning
Yuhui Wang, Qingyuan Wu, Dylan R. Ashley, Francesco Faccio, Weida Li, Chao Huang, Jürgen Schmidhuber Score Matching with Missing Data
Josh Givens, Song Liu, Henry Reeve scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data
Olga Ovcharenko, Florian Barkmann, Philip Toma, Imant Daunhawer, Julia E Vogt, Sebastian Schelter, Valentina Boeva SDMG: Smoothing Your Diffusion Models for Powerful Graph Representation Learning
Junyou Zhu, Langzhou He, Chao Gao, Dongpeng Hou, Zhen Su, Philip S. Yu, Juergen Kurths, Frank Hellmann SEAD: Unsupervised Ensemble of Streaming Anomaly Detectors
Saumya Gaurang Shah, Abishek Sankararaman, Balakrishnan Murali Narayanaswamy, Vikramank Singh Secant Line Search for Frank-Wolfe Algorithms
Deborah Hendrych, Sebastian Pokutta, Mathieu Besançon, David Martı́nez-Rubio SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning
Yong Liu, Di Fu, Shenggan Cheng, Zirui Zhu, Yang Luo, Minhao Cheng, Cho-Jui Hsieh, Yang You Segment Anyword: Mask Prompt Inversion for Open-Set Grounded Segmentation
Zhihua Liu, Amrutha Saseendran, Lei Tong, Xilin He, Fariba Yousefi, Nikolay Burlutskiy, Dino Oglic, Tom Diethe, Philip Alexander Teare, Huiyu Zhou, Chen Jin Selective Preference Aggregation
Shreyas Kadekodi, Hayden Mctavish, Berk Ustun Self-Bootstrapping for Versatile Test-Time Adaptation
Shuaicheng Niu, Guohao Chen, Peilin Zhao, Tianyi Wang, Pengcheng Wu, Zhiqi Shen Self-Consistency Preference Optimization
Archiki Prasad, Weizhe Yuan, Richard Yuanzhe Pang, Jing Xu, Maryam Fazel-Zarandi, Mohit Bansal, Sainbayar Sukhbaatar, Jason E Weston, Jane Yu Self-Cross Feature Based Spiking Neural Networks for Efficient Few-Shot Learning
Qi Xu, Junyang Zhu, Dongdong Zhou, Hao Chen, Yang Liu, Jiangrong Shen, Qiang Zhang Self-Supervised Masked Graph Autoencoder via Structure-Aware Curriculum
Haoyang Li, Xin Wang, Zeyang Zhang, Zongyuan Wu, Linxin Xiao, Wenwu Zhu SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models
Yung-Sung Chuang, Benjamin Cohen-Wang, Zejiang Shen, Zhaofeng Wu, Hu Xu, Xi Victoria Lin, James R. Glass, Shang-Wen Li, Wen-Tau Yih SEMU: Singular Value Decomposition for Efficient Machine Unlearning
Marcin Sendera, Łukasz Struski, Kamil Książek, Kryspin Musiol, Jacek Tabor, Dawid Damian Rymarczyk Separating Knowledge and Perception with Procedural Data
Adrian Rodriguez-Munoz, Manel Baradad, Phillip Isola, Antonio Torralba SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator
Guoxuan Chen, Han Shi, Jiawei Li, Yihang Gao, Xiaozhe Ren, Yimeng Chen, Xin Jiang, Zhenguo Li, Weiyang Liu, Chao Huang SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-Training
Tianzhe Chu, Yuexiang Zhai, Jihan Yang, Shengbang Tong, Saining Xie, Dale Schuurmans, Quoc V Le, Sergey Levine, Yi Ma ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference
Hanshi Sun, Li-Wen Chang, Wenlei Bao, Size Zheng, Ningxin Zheng, Xin Liu, Harry Dong, Yuejie Chi, Beidi Chen SHE: Streaming-Media Hashing Retrieval
Ruitao Pu, Yang Qin, Xiaomin Song, Dezhong Peng, Zhenwen Ren, Yuan Sun SHIELD: Multi-Task Multi-Distribution Vehicle Routing Solver with Sparsity and Hierarchy
Yong Liang Goh, Zhiguang Cao, Yining Ma, Jianan Zhou, Mohammed Haroon Dupty, Wee Sun Lee Shielded Diffusion: Generating Novel and Diverse Images Using Sparse Repellency
Michael Kirchhof, James Thornton, Louis Béthune, Pierre Ablin, Eugene Ndiaye, Marco Cuturi Simple Path Structural Encoding for Graph Transformers
Louis Airale, Antonio Longa, Mattia Rigon, Andrea Passerini, Roberto Passerone Simple Policy Optimization
Zhengpeng Xie, Qiang Zhang, Fan Yang, Marco Hutter, Renjing Xu Simplifying DINO via Coding Rate Regularization
Ziyang Wu, Jingyuan Zhang, Druv Pai, Xudong Wang, Chandan Singh, Jianwei Yang, Jianfeng Gao, Yi Ma Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery
Mateusz Olko, Mateusz Gajewski, Joanna Wojciechowska, Mikołaj Morzy, Piotr Sankowski, Piotr Miłoś SING: Spatial Context in Large Language Model for Next-Gen Wearables
Ayushi Mishra, Yang Bai, Priyadarshan Narayanasamy, Nakul Garg, Nirupam Roy SITCOM: Step-Wise Triple-Consistent Diffusion Sampling for Inverse Problems
Ismail Alkhouri, Shijun Liang, Cheng-Han Huang, Jimmy Dai, Qing Qu, Saiprasad Ravishankar, Rongrong Wang Sketch to Adapt: Fine-Tunable Sketches for Efficient LLM Adaptation
Tianyi Zhang, Junda Su, Aditya Desai, Oscar Wu, Zhaozhuo Xu, Anshumali Shrivastava SkipGPT: Each Token Is One of a Kind
Anhao Zhao, Fanghua Ye, Yingqi Fan, Junlong Tong, Jing Xiong, Zhiwei Fei, Hui Su, Xiaoyu Shen SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting
Yitian Zhang, Liheng Ma, Antonios Valkanas, Boris N. Oreshkin, Mark Coates Sleeping Reinforcement Learning
Simone Drago, Marco Mussi, Alberto Maria Metelli Sliding Puzzles Gym: A Scalable Benchmark for State Representation in Visual Reinforcement Learning
Bryan Lincoln Marques De Oliveira, Luana Guedes Barros Martins, Bruno Brandão, Murilo Lopes Da Luz, Telma Woerle De Lima Soares, Luckeciano Carvalho Melo SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models
Wei Huang, Haotong Qin, Yangdong Liu, Yawei Li, Qinshuo Liu, Xianglong Liu, Luca Benini, Michele Magno, Shiming Zhang, Xiaojuan Qi SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds
Ali Bahri, Moslem Yazdanpanah, Sahar Dastani, Mehrdad Noori, Gustavo Adolfo Vargas Hakim, David Osowiechi, Farzad Beizaee, Ismail Ben Ayed, Christian Desrosiers Smooth Interpolation for Improved Discrete Graph Generative Models
Yuxuan Song, Juntong Shi, Jingjing Gong, Minkai Xu, Stefano Ermon, Hao Zhou, Wei-Ying Ma SNS-Bench: Defining, Building, and Assessing Capabilities of Large Language Models in Social Networking Services
Hongcheng Guo, Yue Wang, Shaosheng Cao, Fei Zhao, Boyang Wang, Lei Li, Liang Chen, Xinze Lyu, Zhe Xu, Yao Hu, Zhoujun Li Socialized Coevolution: Advancing a Better World Through Cross-Task Collaboration
Xinjie Yao, Yu Wang, Pengfei Zhu, Wanyu Lin, Ruipu Zhao, Zhoupeng Guo, Weihao Li, Qinghua Hu SoftMax Is Not Enough (for Sharp Size Generalisation)
Petar Veličković, Christos Perivolaropoulos, Federico Barbero, Razvan Pascanu Solving Zero-Sum Convex Markov Games
Fivos Kalogiannis, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Ian Gemp, Georgios Piliouras SongGen: A Single Stage Auto-Regressive Transformer for Text-to-Song Generation
Zihan Liu, Shuangrui Ding, Zhixiong Zhang, Xiaoyi Dong, Pan Zhang, Yuhang Zang, Yuhang Cao, Dahua Lin, Jiaqi Wang Sortformer: A Novel Approach for Permutation-Resolved Speaker Supervision in Speech-to-Text Systems
Taejin Park, Ivan Medennikov, Kunal Dhawan, Weiqing Wang, He Huang, Nithin Rao Koluguri, Krishna C Puvvada, Jagadeesh Balam, Boris Ginsburg Sounding That Object: Interactive Object-Aware Image to Audio Generation
Tingle Li, Baihe Huang, Xiaobin Zhuang, Dongya Jia, Jiawei Chen, Yuping Wang, Zhuo Chen, Gopala Anumanchipalli, Yuxuan Wang Sparse Autoencoders for Hypothesis Generation
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