NeurIPS 2023
3540 papers
(Amplified) Banded Matrix Factorization: A Unified Approach to Private Training
Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, John Rush, Abhradeep Guha Thakurta, Zheng Xu $\texttt{TACO}$: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
Ruijie Zheng, Xiyao Wang, Yanchao Sun, Shuang Ma, Jieyu Zhao, Huazhe Xu, Hal Daumé Iii, Furong Huang $\varepsilon$-Fractional Core Stability in Hedonic Games.
Simone Fioravanti, Michele Flammini, Bojana Kodric, Giovanna Varricchio $k$-Means Clustering with Distance-Based Privacy
Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong 3D Copy-Paste: Physically Plausible Object Insertion for Monocular 3D Detection
Yunhao Ge, Hong-Xing Yu, Cheng Zhao, Yuliang Guo, Xinyu Huang, Liu Ren, Laurent Itti, Jiajun Wu 3D Indoor Instance Segmentation in an Open-World
Mohamed El Amine Boudjoghra, Salwa Al Khatib, Jean Lahoud, Hisham Cholakkal, Rao Anwer, Salman H Khan, Fahad Shahbaz Khan 3D Molecule Generation by Denoising Voxel Grids
Pedro O O. Pinheiro, Joshua Rackers, Joseph Kleinhenz, Michael Maser, Omar Mahmood, Andrew Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi 3D-Aware Visual Question Answering About Parts, Poses and Occlusions
Xingrui Wang, Wufei Ma, Zhuowan Li, Adam Kortylewski, Alan L. Yuille 3D-LLM: Injecting the 3D World into Large Language Models
Yining Hong, Haoyu Zhen, Peihao Chen, Shuhong Zheng, Yilun Du, Zhenfang Chen, Chuang Gan 4D Panoptic Scene Graph Generation
Jingkang Yang, Jun Cen, Wenxuan Peng, Shuai Liu, Fangzhou Hong, Xiangtai Li, Kaiyang Zhou, Qifeng Chen, Ziwei Liu 4m: Massively Multimodal Masked Modeling
David Mizrahi, Roman Bachmann, Oguzhan Kar, Teresa Yeo, Mingfei Gao, Afshin Dehghan, Amir Zamir A Bounded Ability Estimation for Computerized Adaptive Testing
Yan Zhuang, Qi Liu, Guanhao Zhao, Zhenya Huang, Weizhe Huang, Zachary Pardos, Enhong Chen, Jinze Wu, Xin Li A Case for Reframing Automated Medical Image Classification as Segmentation
Sarah Hooper, Mayee Chen, Khaled Saab, Kush Bhatia, Curtis Langlotz, Christopher Ré A Comprehensive Benchmark for Neural Human Radiance Fields
Kenkun Liu, Derong Jin, Ailing Zeng, Xiaoguang Han, Lei Zhang A Comprehensive Study on Text-Attributed Graphs: Benchmarking and Rethinking
Hao Yan, Chaozhuo Li, Ruosong Long, Chao Yan, Jianan Zhao, Wenwen Zhuang, Jun Yin, Peiyan Zhang, Weihao Han, Hao Sun, Weiwei Deng, Qi Zhang, Lichao Sun, Xing Xie, Senzhang Wang A Computationally Efficient Sparsified Online Newton Method
Fnu Devvrit, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S. Dhillon A Cross-Moment Approach for Causal Effect Estimation
Yaroslav Kivva, Saber Salehkaleybar, Negar Kiyavash A Dataset of Relighted 3D Interacting Hands
Gyeongsik Moon, Shunsuke Saito, Weipeng Xu, Rohan Joshi, Julia Buffalini, Harley Bellan, Nicholas Rosen, Jesse Richardson, Mallorie Mize, Philippe De Bree, Tomas Simon, Bo Peng, Shubham Garg, Kevyn McPhail, Takaaki Shiratori A Definition of Continual Reinforcement Learning
David Abel, Andre Barreto, Benjamin Van Roy, Doina Precup, Hado P van Hasselt, Satinder P. Singh A Diffusion-Model of Joint Interactive Navigation
Matthew Niedoba, Jonathan Lavington, Yunpeng Liu, Vasileios Lioutas, Justice Sefas, Xiaoxuan Liang, Dylan Green, Setareh Dabiri, Berend Zwartsenberg, Adam Scibior, Frank Wood A Dynamical System View of Langevin-Based Non-Convex Sampling
Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause A Fast Heuristic to Optimize Time-Space Tradeoff for Large Models
Akifumi Imanishi, Zijian Xu, Masayuki Takagi, Sixue Wang, Emilio Castillo A Fractional Graph Laplacian Approach to Oversmoothing
Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok A General Framework for Equivariant Neural Networks on Reductive Lie Groups
Ilyes Batatia, Mario Geiger, Jose Munoz, Tess Smidt, Lior Silberman, Christoph Ortner A General Theory of Correct, Incorrect, and Extrinsic Equivariance
Dian Wang, Xupeng Zhu, Jung Yeon Park, Mingxi Jia, Guanang Su, Robert Platt, Robin Walters A Guide Through the Zoo of Biased SGD
Yury Demidovich, Grigory Malinovsky, Igor Sokolov, Peter Richtarik A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction
Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy A Heavy-Tailed Algebra for Probabilistic Programming
Feynman T Liang, Liam Hodgkinson, Michael W. Mahoney A Hierarchical Spatial Transformer for Massive Point Samples in Continuous Space
Wenchong He, Zhe Jiang, Tingsong Xiao, Zelin Xu, Shigang Chen, Ronald Fick, Miles Medina, Christine Angelini A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation
Thomas Fel, Victor Boutin, Louis Béthune, Remi Cadene, Mazda Moayeri, Léo Andéol, Mathieu Chalvidal, Thomas Serre A Measure-Theoretic Axiomatisation of Causality
Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet A New Perspective on Building Efficient and Expressive 3D Equivariant Graph Neural Networks
Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla P. Gomes, Zhi-Ming Ma A Normative Theory of Social Conflict
Sergey Shuvaev, Evgeny Amelchenko, Dmitry Smagin, Natalia Kudryavtseva, Grigori Enikolopov, Alex Koulakov A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective
Chenhang Cui, Yazhou Ren, Jingyu Pu, Jiawei Li, Xiaorong Pu, Tianyi Wu, Yutao Shi, Lifang He A Path to Simpler Models Starts with Noise
Lesia Semenova, Harry Chen, Ronald Parr, Cynthia Rudin A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning
Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C. Bayan Bruss, Andrew G Wilson, Tom Goldstein, Micah Goldblum A Privacy-Friendly Approach to Data Valuation
Jiachen Wang, Yuqing Zhu, Yu-Xiang Wang, Ruoxi Jia, Prateek Mittal A Randomized Approach to Tight Privacy Accounting
Jiachen Wang, Saeed Mahloujifar, Tong Wu, Ruoxi Jia, Prateek Mittal A Rigorous Link Between Deep Ensembles and (Variational) Bayesian Methods
Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch A Robust and Opponent-Aware League Training Method for StarCraft II
Ruozi Huang, Xipeng Wu, Hongsheng Yu, Zhong Fan, Haobo Fu, Qiang Fu, Wei Yang A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models
Alexander Reisach, Myriam Tami, Christof Seiler, Antoine Chambaz, Sebastian Weichwald A Spectral Theory of Neural Prediction and Alignment
Abdulkadir Canatar, Jenelle Feather, Albert Wakhloo, SueYeon Chung A State Representation for Diminishing Rewards
Ted Moskovitz, Samo Hromadka, Ahmed Touati, Diana Borsa, Maneesh Sahani A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset
Zahra Gharaee, ZeMing Gong, Nicholas Pellegrino, Iuliia Zarubiieva, Joakim Bruslund Haurum, Scott Lowe, Jaclyn McKeown, Chris Ho, Joschka McLeod, Yi-Yun Wei, Jireh Agda, Sujeevan Ratnasingham, Dirk Steinke, Angel Chang, Graham W. Taylor, Paul Fieguth A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence
Junyi Zhang, Charles Herrmann, Junhwa Hur, Luisa Polania Cabrera, Varun Jampani, Deqing Sun, Ming-Hsuan Yang A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression
Tin Sum Cheng, Aurelien Lucchi, Anastasis Kratsios, Ivan Dokmanić, David Belius A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning
Florian Felten, Lucas N. Alegre, Ann Nowe, Ana Bazzan, El Ghazali Talbi, Grégoire Danoy, Bruno C. da Silva A Unified Conditional Framework for Diffusion-Based Image Restoration
Yi Zhang, Xiaoyu Shi, Dasong Li, Xiaogang Wang, Jian Wang, Hongsheng Li A Unified Detection Framework for Inference-Stage Backdoor Defenses
Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding A Unified Framework for U-Net Design and Analysis
Christopher K. I. Williams, Fabian Falck, George Deligiannidis, Chris C Holmes, Arnaud Doucet, Saifuddin Syed A Unified Model and Dimension for Interactive Estimation
Nataly Brukhim, Miro Dudik, Aldo Pacchiano, Robert E. Schapire A Unified, Scalable Framework for Neural Population Decoding
Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael Mendelson, Blake Richards, Matthew Perich, Guillaume Lajoie, Eva Dyer A Variational Perspective on High-Resolution ODEs
Hoomaan Maskan, Konstantinos Zygalakis, Alp Yurtsever A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference
Emile van Krieken, Thiviyan Thanapalasingam, Jakub Tomczak, Frank van Harmelen, Annette Ten Teije A*Net: A Scalable Path-Based Reasoning Approach for Knowledge Graphs
Zhaocheng Zhu, Xinyu Yuan, Michael Galkin, Louis-Pascal Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang AbDiffuser: Full-Atom Generation of In-Vitro Functioning Antibodies
Karolis Martinkus, Jan Ludwiczak, Wei-Ching Liang, Julien Lafrance-Vanasse, Isidro Hotzel, Arvind Rajpal, Yan Wu, Kyunghyun Cho, Richard Bonneau, Vladimir Gligorijevic, Andreas Loukas AbdomenAtlas-8k: Annotating 8,000 CT Volumes for Multi-Organ Segmentation in Three Weeks
Chongyu Qu, Tiezheng Zhang, Hualin Qiao, Jie Liu, Yucheng Tang, Alan L. Yuille, Zongwei Zhou Accelerated Zeroth-Order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance
Nikita Kornilov, Ohad Shamir, Aleksandr Lobanov, Darina Dvinskikh, Alexander Gasnikov, Innokentiy Shibaev, Eduard Gorbunov, Samuel Horváth Accelerating Exploration with Unlabeled Prior Data
Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine Accelerating Molecular Graph Neural Networks via Knowledge Distillation
Filip Ekström Kelvinius, Dimitar Georgiev, Artur Toshev, Johannes Gasteiger Accelerating Motion Planning via Optimal Transport
An T. Le, Georgia Chalvatzaki, Armin Biess, Jan R Peters Active Bipartite Ranking
James Cheshire, Vincent Laurent, Stephan Clémençon Active Learning for Semantic Segmentation with Multi-Class Label Query
Sehyun Hwang, Sohyun Lee, Hoyoung Kim, Minhyeon Oh, Jungseul Ok, Suha Kwak Active Learning-Based Species Range Estimation
Christian Lange, Elijah Cole, Grant Van Horn, Oisin Mac Aodha Active Negative Loss Functions for Learning with Noisy Labels
Xichen Ye, Xiaoqiang Li, Songmin Dai, Tong Liu, Yan Sun, Weiqin Tong Active Observing in Continuous-Time Control
Samuel Holt, Alihan Hüyük, Mihaela van der Schaar Active Reasoning in an Open-World Environment
Manjie Xu, Guangyuan Jiang, Wei Liang, Chi Zhang, Yixin Zhu Activity Grammars for Temporal Action Segmentation
Dayoung Gong, Joonseok Lee, Deunsol Jung, Suha Kwak, Minsu Cho AD-PT: Autonomous Driving Pre-Training with Large-Scale Point Cloud Dataset
Jiakang Yuan, Bo Zhang, Xiangchao Yan, Botian Shi, Tao Chen, Yikang Li, Yu Qiao AdANNS: A Framework for Adaptive Semantic Search
Aniket Rege, Aditya Kusupati, Sharan Ranjit S, Alan Fan, Qingqing Cao, Sham Kakade, Prateek Jain, Ali Farhadi Adapting Neural Link Predictors for Data-Efficient Complex Query Answering
Erik Arakelyan, Pasquale Minervini, Daniel Daza, Michael Cochez, Isabelle Augenstein Adaptive Linear Estimating Equations
Mufang Ying, Koulik Khamaru, Cun-Hui Zhang Adaptive Online Replanning with Diffusion Models
Siyuan Zhou, Yilun Du, Shun Zhang, Mengdi Xu, Yikang Shen, Wei Xiao, Dit-Yan Yeung, Chuang Gan Adaptive Privacy Composition for Accuracy-First Mechanisms
Ryan M Rogers, Gennady Samorodnitsk, Steven Z. Wu, Aaditya Ramdas AdaptSSR: Pre-Training User Model with Augmentation-Adaptive Self-Supervised Ranking
Yang Yu, Qi Liu, Kai Zhang, Yuren Zhang, Chao Song, Min Hou, Yuqing Yuan, Zhihao Ye, Zaixi Zhang, Sanshi Lei Yu Add and Thin: Diffusion for Temporal Point Processes
David Lüdke, Marin Biloš, Oleksandr Shchur, Marten Lienen, Stephan Günnemann Addressing Negative Transfer in Diffusion Models
Hyojun Go, Kim, Yunsung Lee, Seunghyun Lee, Shinhyeok Oh, Hyeongdon Moon, Seungtaek Choi ADGym: Design Choices for Deep Anomaly Detection
Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao Adversarial Attacks on Online Learning to Rank with Click Feedback
Jinhang Zuo, Zhiyao Zhang, Zhiyong Wang, Shuai Li, Mohammad Hajiesmaili, Adam Wierman Adversarial Counterfactual Environment Model Learning
Xiong-Hui Chen, Yang Yu, Zhengmao Zhu, ZhiHua Yu, Chen Zhenjun, Chenghe Wang, Yinan Wu, Rong-Jun Qin, Hongqiu Wu, Ruijin Ding, Huang Fangsheng Adversarial Examples Are Not Real Features
Ang Li, Yifei Wang, Yiwen Guo, Yisen Wang Adversarial Learning for Feature Shift Detection and Correction
Míriam Barrabés, Daniel Mas Montserrat, Margarita Geleta, Xavier Giró-i-Nieto, Alexander Ioannidis Adversarial Model for Offline Reinforcement Learning
Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann Adversarial Training from Mean Field Perspective
Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki Affinity-Aware Graph Networks
Ameya Velingker, Ali Sinop, Ira Ktena, Petar Veličković, Sreenivas Gollapudi Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
Tom Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi Agnostic Multi-Group Active Learning
Nicholas Rittler, Kamalika Chaudhuri Agnostically Learning Single-Index Models Using Omnipredictors
Aravind Gollakota, Parikshit Gopalan, Adam Klivans, Konstantinos Stavropoulos AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning
Mohammadamin Tavakoli, Pierre Baldi, Ann Marie Carlton, Yin Ting Chiu, Alexander Shmakov, David Van Vranken AiluRus: A Scalable ViT Framework for Dense Prediction
Jin Li, Yaoming Wang, Xiaopeng Zhang, Bowen Shi, Dongsheng Jiang, Chenglin Li, Wenrui Dai, Hongkai Xiong, Qi Tian AIMS: All-Inclusive Multi-Level Segmentation for Anything
Lu Qi, Jason Kuen, Weidong Guo, Jiuxiang Gu, Zhe Lin, Bo Du, Yu Xu, Ming-Hsuan Yang AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs
Adam Cobb, Anirban Roy, Daniel Elenius, Frederick Heim, Brian Swenson, Sydney Whittington, James Walker, Theodore Bapty, Joseph Hite, Karthik Ramani, Christopher McComb, Susmit Jha Alexa Arena: A User-Centric Interactive Platform for Embodied AI
Qiaozi Gao, Govind Thattai, Suhaila Shakiah, Xiaofeng Gao, Shreyas Pansare, Vasu Sharma, Gaurav Sukhatme, Hangjie Shi, Bofei Yang, Desheng Zhang, Lucy Hu, Karthika Arumugam, Shui Hu, Matthew Wen, Dinakar Guthy, Shunan Chung, Rohan Khanna, Osman Ipek, Leslie Ball, Kate Bland, Heather Rocker, Michael Johnston, Reza Ghanadan, Dilek Hakkani-Tur, Prem Natarajan Align Your Prompts: Test-Time Prompting with Distribution Alignment for Zero-Shot Generalization
Jameel Abdul Samadh, Mohammad Hanan Gani, Noor Hussein, Muhammad Uzair Khattak, Muhammad Muzammal Naseer, Fahad Shahbaz Khan, Salman H Khan Aligning Gradient and Hessian for Neural Signed Distance Function
Ruian Wang, Zixiong Wang, Yunxiao Zhang, Shuangmin Chen, Shiqing Xin, Changhe Tu, Wenping Wang AlpacaFarm: A Simulation Framework for Methods That Learn from Human Feedback
Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B Hashimoto Alternating Updates for Efficient Transformers
Cenk Baykal, Dylan Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang Alternation Makes the Adversary Weaker in Two-Player Games
Volkan Cevher, Ashok Cutkosky, Ali Kavis, Georgios Piliouras, Stratis Skoulakis, Luca Viano Amazon-M2: A Multilingual Multi-Locale Shopping Session Dataset for Recommendation and Text Generation
Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang Ambient Diffusion: Learning Clean Distributions from Corrupted Data
Giannis Daras, Kulin Shah, Yuval Dagan, Aravind Gollakota, Alex Dimakis, Adam Klivans American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers
Melissa Dell, Jacob Carlson, Tom Bryan, Emily Silcock, Abhishek Arora, Zejiang Shen, Luca D'Amico-Wong, Quan Le, Pablo Querubin, Leander Heldring An Inductive Bias for Tabular Deep Learning
Ege Beyazit, Jonathan Kozaczuk, Bo Li, Vanessa Wallace, Bilal Fadlallah An Information Theory Perspective on Variance-Invariance-Covariance Regularization
Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun An Information-Theoretic Quantification of the Content of Communication Between Brain Regions
Marco Celotto, Jan Bím, Alejandro Tlaie, Vito De Feo, Alessandro Toso, Stefan Lemke, Daniel Chicharro, Hamed Nili, Malte Bieler, Ileana Hanganu-Opatz, Tobias Donner, Andrea Brovelli, Stefano Panzeri Analyzing Generalization of Neural Networks Through Loss Path Kernels
Yilan Chen, Wei Huang, Hao Wang, Charlotte Loh, Akash Srivastava, Lam Nguyen, Lily Weng Anchor Data Augmentation
Nora Schneider, Shirin Goshtasbpour, Fernando Perez-Cruz AndroidInTheWild: A Large-Scale Dataset for Android Device Control
Christopher Rawles, Alice Li, Daniel Rodriguez, Oriana Riva, Timothy Lillicrap ANPL: Towards Natural Programming with Interactive Decomposition
Di Huang, Ziyuan Nan, Xing Hu, Pengwei Jin, Shaohui Peng, Yuanbo Wen, Rui Zhang, Zidong Du, Qi Guo, Yewen Pu, Yunji Chen Any-to-Any Generation via Composable Diffusion
Zineng Tang, Ziyi Yang, Chenguang Zhu, Michael Zeng, Mohit Bansal Anytime Model Selection in Linear Bandits
Parnian Kassraie, Nicolas Emmenegger, Andreas Krause, Aldo Pacchiano Anytime-Competitive Reinforcement Learning with Policy Prior
Jianyi Yang, Pengfei Li, Tongxin Li, Adam Wierman, Shaolei Ren Approximately Equivariant Graph Networks
Ningyuan Huang, Ron Levie, Soledad Villar AQuA: A Benchmarking Tool for Label Quality Assessment
Mononito Goswami, Vedant Sanil, Arjun Choudhry, Arvind Srinivasan, Chalisa Udompanyawit, Artur Dubrawski AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation
Tong Wu, Zhihao Fan, Xiao Liu, Hai-Tao Zheng, Yeyun Gong, Yelong Shen, Jian Jiao, Juntao Li, Zhongyu Wei, Jian Guo, Nan Duan, Weizhu Chen Arbitrarily Scalable Environment Generators via Neural Cellular Automata
Yulun Zhang, Matthew Fontaine, Varun Bhatt, Stefanos Nikolaidis, Jiaoyang Li Are Aligned Neural Networks Adversarially Aligned?
Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Pang Wei W Koh, Daphne Ippolito, Florian Tramer, Ludwig Schmidt Are Diffusion Models Vision-and-Language Reasoners?
Benno Krojer, Elinor Poole-Dayan, Vikram Voleti, Chris Pal, Siva Reddy Are GATs Out of Balance?
Nimrah Mustafa, Aleksandar Bojchevski, Rebekka Burkholz ARTIC3D: Learning Robust Articulated 3D Shapes from Noisy Web Image Collections
Chun-Han Yao, Amit Raj, Wei-Chih Hung, Michael Rubinstein, Yuanzhen Li, Ming-Hsuan Yang, Varun Jampani ASIF: Coupled Data Turns Unimodal Models to Multimodal Without Training
Antonio Norelli, Marco Fumero, Valentino Maiorca, Luca Moschella, Emanuele Rodolà, Francesco Locatello ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition
Aashaka Desai, Lauren Berger, Fyodor Minakov, Nessa Milano, Chinmay Singh, Kriston Pumphrey, Richard E. Ladner, Hal Daumé Iii, Alex X Lu, Naomi Caselli, Danielle Bragg Assessor360: Multi-Sequence Network for Blind Omnidirectional Image Quality Assessment
Tianhe Wu, Shuwei Shi, Haoming Cai, Mingdeng Cao, Jing Xiao, Yinqiang Zheng, Yujiu Yang Assumption Violations in Causal Discovery and the Robustness of Score Matching
Francesco Montagna, Atalanti Mastakouri, Elias Eulig, Nicoletta Noceti, Lorenzo Rosasco, Dominik Janzing, Bryon Aragam, Francesco Locatello Asynchrony-Robust Collaborative Perception via Bird's Eye View Flow
Sizhe Wei, Yuxi Wei, Yue Hu, Yifan Lu, Yiqi Zhong, Siheng Chen, Ya Zhang ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation
Björn Deiseroth, Mayukh Deb, Samuel Weinbach, Manuel Brack, Patrick Schramowski, Kristian Kersting Attacks on Online Learners: A Teacher-Student Analysis
Riccardo Giuseppe Margiotta, Sebastian Goldt, Guido Sanguinetti AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models
Yuancheng Wang, Zeqian Ju, Xu Tan, Lei He, Zhizheng Wu, Jiang Bian, Sheng Zhao Auditing Fairness by Betting
Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas Auditing for Human Expertise
Rohan Alur, Loren Laine, Darrick Li, Manish Raghavan, Devavrat Shah, Dennis Shung Augmentation-Aware Self-Supervision for Data-Efficient GAN Training
Liang Hou, Qi Cao, Yige Yuan, Songtao Zhao, Chongyang Ma, Siyuan Pan, Pengfei Wan, Zhongyuan Wang, Huawei Shen, Xueqi Cheng Augmenting Language Models with Long-Term Memory
Weizhi Wang, Li Dong, Hao Cheng, Xiaodong Liu, Xifeng Yan, Jianfeng Gao, Furu Wei Autodecoding Latent 3D Diffusion Models
Evangelos Ntavelis, Aliaksandr Siarohin, Kyle Olszewski, Chaoyang Wang, Luc V Gool, Sergey Tulyakov AutoGO: Automated Computation Graph Optimization for Neural Network Evolution
Mohammad Salameh, Keith Mills, Negar Hassanpour, Fred Han, Shuting Zhang, Wei Lu, Shangling Jui, Chunhua Zhou, Fengyu Sun, Di Niu Automated Classification of Model Errors on ImageNet
Momchil Peychev, Mark Müller, Marc Fischer, Martin Vechev AVIDa-hIL6: A Large-Scale VHH Dataset Produced from an Immunized Alpaca for Predicting Antigen-Antibody Interactions
Hirofumi Tsuruta, Hiroyuki Yamazaki, Ryota Maeda, Ryotaro Tamura, Jennifer Wei, Zelda E. Mariet, Poomarin Phloyphisut, Hidetoshi Shimokawa, Joseph R. Ledsam, Lucy Colwell, Akihiro Imura AVIS: Autonomous Visual Information Seeking with Large Language Model Agent
Ziniu Hu, Ahmet Iscen, Chen Sun, Kai-Wei Chang, Yizhou Sun, David A. Ross, Cordelia Schmid, Alireza Fathi BadTrack: A Poison-Only Backdoor Attack on Visual Object Tracking
Bin Huang, Jiaqian Yu, Yiwei Chen, Siyang Pan, Qiang Wang, Zhi Wang Balanced Training for Sparse GANs
Yite Wang, Jing Wu, Naira Hovakimyan, Ruoyu Sun Balancing Memorization and Generalization in RNNs for High Performance Brain-Machine Interfaces
Joseph Costello, Hisham Temmar, Luis Cubillos, Matthew Mender, Dylan Wallace, Matt Willsey, Parag Patil, Cynthia Chestek Bandit Social Learning Under Myopic Behavior
Kiarash Banihashem, MohammadTaghi Hajiaghayi, Suho Shin, Aleksandrs Slivkins Bandit Task Assignment with Unknown Processing Time
Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Ken-Ichi Kawarabayashi BanditPAM++: Faster $k$-Medoids Clustering
Mo Tiwari, Ryan Kang, Donghyun Lee, Sebastian Thrun, Ilan Shomorony, Martin J Zhang Batch Bayesian Optimization for Replicable Experimental Design
Zhongxiang Dai, Quoc Phong Nguyen, Sebastian Tay, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low, Patrick Jaillet BatchNorm Allows Unsupervised Radial Attacks
Amur Ghose, Apurv Gupta, Yaoliang Yu, Pascal Poupart Battle of the Backbones: A Large-Scale Comparison of Pretrained Models Across Computer Vision Tasks
Micah Goldblum, Hossein Souri, Renkun Ni, Manli Shu, Viraj Prabhu, Gowthami Somepalli, Prithvijit Chattopadhyay, Mark Ibrahim, Adrien Bardes, Judy Hoffman, Rama Chellappa, Andrew G Wilson, Tom Goldstein BayesDAG: Gradient-Based Posterior Inference for Causal Discovery
Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong Bayesian Optimisation of Functions on Graphs
Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A Osborne, Xiaowen Dong Bayesian Optimization with Cost-Varying Variable Subsets
Sebastian Tay, Chuan Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset
Jiaming Ji, Mickel Liu, Josef Dai, Xuehai Pan, Chi Zhang, Ce Bian, Boyuan Chen, Ruiyang Sun, Yizhou Wang, Yaodong Yang Behavior Alignment via Reward Function Optimization
Dhawal Gupta, Yash Chandak, Scott Jordan, Philip S. Thomas, Bruno C. da Silva BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic Parsing
Subhro Roy, Samuel Thomson, Tongfei Chen, Richard Shin, Adam Pauls, Jason Eisner, Benjamin Van Durme Benchmark of Machine Learning Force Fields for Semiconductor Simulations: Datasets, Metrics, and Comparative Analysis
Geonu Kim, Byunggook Na, Gunhee Kim, Hyuntae Cho, Seungjin Kang, Hee Sun Lee, Saerom Choi, Heejae Kim, Seungwon Lee, Yongdeok Kim Benchmarking Foundation Models with Language-Model-as-an-Examiner
Yushi Bai, Jiahao Ying, Yixin Cao, Xin Lv, Yuze He, Xiaozhi Wang, Jifan Yu, Kaisheng Zeng, Yijia Xiao, Haozhe Lyu, Jiayin Zhang, Juanzi Li, Lei Hou Benchmarking Large Language Models on CMExam - A Comprehensive Chinese Medical Exam Dataset
Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, Michael Lingzhi Li Benchmarking Robustness to Adversarial Image Obfuscations
Florian Stimberg, Ayan Chakrabarti, Chun-Ta Lu, Hussein Hazimeh, Otilia Stretcu, Wei Qiao, Yintao Liu, Merve Kaya, Cyrus Rashtchian, Ariel Fuxman, Mehmet Tek, Sven Gowal BERT Lost Patience Won't Be Robust to Adversarial Slowdown
Zachary Coalson, Gabriel Ritter, Rakesh Bobba, Sanghyun Hong Beta Diffusion
Mingyuan Zhou, Tianqi Chen, Zhendong Wang, Huangjie Zheng Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks
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Tao Lei, Junwen Bai, Siddhartha Brahma, Joshua Ainslie, Kenton Lee, Yanqi Zhou, Nan Du, Vincent Zhao, Yuexin Wu, Bo Li, Yu Zhang, Ming-Wei Chang Conditional Matrix Flows for Gaussian Graphical Models
Marcello Massimo Negri, Fabricio Arend Torres, Volker Roth Coneheads: Hierarchy Aware Attention
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Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang Counterfactual Memorization in Neural Language Models
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Lucy Xiaoyang Shi, Yunfan Jiang, Jake Grigsby, Linxi Fan, Yuke Zhu CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion
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Qihe Huang, Lei Shen, Ruixin Zhang, Shouhong Ding, Binwu Wang, Zhengyang Zhou, Yang Wang Crystal Structure Prediction by Joint Equivariant Diffusion
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Joshua Southern, Jeremy Wayland, Michael Bronstein, Bastian Rieck Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models
Julien Siems, Konstantin Ditschuneit, Winfried Ripken, Alma Lindborg, Maximilian Schambach, Johannes Otterbach, Martin Genzel Customizable Image Synthesis with Multiple Subjects
Zhiheng Liu, Yifei Zhang, Yujun Shen, Kecheng Zheng, Kai Zhu, Ruili Feng, Yu Liu, Deli Zhao, Jingren Zhou, Yang Cao CWCL: Cross-Modal Transfer with Continuously Weighted Contrastive Loss
Rakshith Sharma Srinivasa, Jaejin Cho, Chouchang Yang, Yashas Malur Saidutta, Ching-Hua Lee, Yilin Shen, Hongxia Jin D-Separation for Causal Self-Explanation
Wei Liu, Jun Wang, Haozhao Wang, Ruixuan Li, Zhiying Deng, YuanKai Zhang, Yang Qiu DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation
Jiuhn Song, Seonghoon Park, Honggyu An, Seokju Cho, Min-Seop Kwak, Sungjin Cho, Seungryong Kim Data Market Design Through Deep Learning
Sai Srivatsa Ravindranath, Yanchen Jiang, David C. Parkes Data Pruning via Moving-One-Sample-Out
Haoru Tan, Sitong Wu, Fei Du, Yukang Chen, Zhibin Wang, Fan Wang, Xiaojuan Qi Data Quality in Imitation Learning
Suneel Belkhale, Yuchen Cui, Dorsa Sadigh Data Selection for Language Models via Importance Resampling
Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang Data-Centric Learning from Unlabeled Graphs with Diffusion Model
Gang Liu, Eric Inae, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang Data-Driven Network Neuroscience: On Data Collection and Benchmark
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Chenyangguang Zhang, Yan Di, Ruida Zhang, Guangyao Zhai, Fabian Manhardt, Federico Tombari, Xiangyang Ji Debiased and Denoised Entity Recognition from Distant Supervision
Haobo Wang, Yiwen Dong, Ruixuan Xiao, Fei Huang, Gang Chen, Junbo Zhao Debiasing Pretrained Generative Models by Uniformly Sampling Semantic Attributes
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Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang, Chenhui Zhang, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li Decompose a Task into Generalizable Subtasks in Multi-Agent Reinforcement Learning
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Yanhui Guo, Xinxin Zuo, Peng Dai, Juwei Lu, Xiaolin Wu, Li Cheng, Youliang Yan, Songcen Xu, Xiaofei Wu Deductive Verification of Chain-of-Thought Reasoning
Zhan Ling, Yunhao Fang, Xuanlin Li, Zhiao Huang, Mingu Lee, Roland Memisevic, Hao Su Deep Contract Design via Discontinuous Networks
Tonghan Wang, Paul Duetting, Dmitry Ivanov, Inbal Talgam-Cohen, David C. Parkes Deep Equilibrium Based Neural Operators for Steady-State PDEs
Tanya Marwah, Ashwini Pokle, J. Zico Kolter, Zachary Lipton, Jianfeng Lu, Andrej Risteski Deep Fractional Fourier Transform
Hu Yu, Jie Huang, Lingzhi Li, Man Zhou, Feng Zhao Deep Insights into Noisy Pseudo Labeling on Graph Data
Botao Wang, Jia Li, Yang Liu, Jiashun Cheng, Yu Rong, Wenjia Wang, Fugee Tsung Deep Momentum Multi-Marginal Schrödinger Bridge
Tianrong Chen, Guan-Horng Liu, Molei Tao, Evangelos Theodorou Deep Patch Visual Odometry
Zachary Teed, Lahav Lipson, Jia Deng Deep Recurrent Optimal Stopping
Niranjan Damera Venkata, Chiranjib Bhattacharyya Deep Reinforcement Learning with Plasticity Injection
Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, Andre Barreto Deep Stochastic Processes via Functional Markov Transition Operators
Jin Xu, Emilien Dupont, Kaspar Märtens, Thomas Rainforth, Yee Whye Teh DeepPCR: Parallelizing Sequential Operations in Neural Networks
Federico Danieli, Miguel Sarabia, Xavier Suau Cuadros, Pau Rodriguez, Luca Zappella Defending Against Data-Free Model Extraction by Distributionally Robust Defensive Training
Zhenyi Wang, Li Shen, Tongliang Liu, Tiehang Duan, Yanjun Zhu, Donglin Zhan, David Doermann, Mingchen Gao Defending Pre-Trained Language Models as Few-Shot Learners Against Backdoor Attacks
Zhaohan Xi, Tianyu Du, Changjiang Li, Ren Pang, Shouling Ji, Jinghui Chen, Fenglong Ma, Ting Wang Delegated Classification
Eden Saig, Inbal Talgam-Cohen, Nir Rosenfeld DELIFFAS: Deformable Light Fields for Fast Avatar Synthesis
Youngjoong Kwon, Lingjie Liu, Henry Fuchs, Marc Habermann, Christian Theobalt Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang Dense and Aligned Captions (DAC) Promote Compositional Reasoning in VL Models
Sivan Doveh, Assaf Arbelle, Sivan Harary, Roei Herzig, Donghyun Kim, Paola Cascante-Bonilla, Amit Alfassy, Rameswar Panda, Raja Giryes, Rogerio Feris, Shimon Ullman, Leonid Karlinsky Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel
Valerii Likhosherstov, Krzysztof M Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamas Sarlos, Adrian Weller Designing Robust Transformers Using Robust Kernel Density Estimation
Xing Han, Tongzheng Ren, Tan Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho DICES Dataset: Diversity in Conversational AI Evaluation for Safety
Lora Aroyo, Alex Taylor, Mark Díaz, Christopher Homan, Alicia Parrish, Gregory Serapio-García, Vinodkumar Prabhakaran, Ding Wang DiffComplete: Diffusion-Based Generative 3D Shape Completion
Ruihang Chu, Enze Xie, Shentong Mo, Zhenguo Li, Matthias Niessner, Chi-Wing Fu, Jiaya Jia Differentiable Clustering with Perturbed Spanning Forests
Lawrence Stewart, Francis R. Bach, Felipe Llinares-Lopez, Quentin Berthet Differentiable Random Partition Models
Thomas Sutter, Alain Ryser, Joram Liebeskind, Julia Vogt Differentiable Sorting for Censored Time-to-Event Data.
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Luca Lanzendörfer, Florian Grötschla, Emil Funke, Roger Wattenhofer Discover and Align Taxonomic Context Priors for Open-World Semi-Supervised Learning
Yu Wang, Zhun Zhong, Pengchong Qiao, Xuxin Cheng, Xiawu Zheng, Chang Liu, Nicu Sebe, Rongrong Ji, Jie Chen Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design
Matthew T Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Greg Farquhar, Shimon Whiteson, Jakob Foerster DISCS: A Benchmark for Discrete Sampling
Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering
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Xiangzhi Chen, Le Wu, Fei Liu, Lei Chen, Kun Zhang, Richang Hong, Meng Wang Dissecting Chain-of-Thought: Compositionality Through In-Context Filtering and Learning
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Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, Colin A Raffel Distributed Personalized Empirical Risk Minimization
Yuyang Deng, Mohammad Mahdi Kamani, Pouria Mahdavinia, Mehrdad Mahdavi Distribution Learnability and Robustness
Shai Ben-David, Alex Bie, Gautam Kamath, Tosca Lechner Distributional Pareto-Optimal Multi-Objective Reinforcement Learning
Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley Llorens Distributionally Robust Linear Quadratic Control
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Shentong Mo, Enze Xie, Ruihang Chu, Lanqing Hong, Matthias Niessner, Zhenguo Li Diverse Community Data for Benchmarking Data Privacy Algorithms
Aniruddha Sen, Christine Task, Dhruv Kapur, Gary Howarth, Karan Bhagat Diversify Your Vision Datasets with Automatic Diffusion-Based Augmentation
Lisa Dunlap, Alyssa Umino, Han Zhang, Jiezhi Yang, Joseph E Gonzalez, Trevor Darrell Django: Detecting Trojans in Object Detection Models via Gaussian Focus Calibration
Guangyu Shen, Siyuan Cheng, Guanhong Tao, Kaiyuan Zhang, Yingqi Liu, Shengwei An, Shiqing Ma, Xiangyu Zhang Do Not Marginalize Mechanisms, Rather Consolidate!
Moritz Willig, Matej Zečević, Devendra Dhami, Kristian Kersting Does Graph Distillation See like Vision Dataset Counterpart?
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Chen Sun, Calvin Luo, Xingyi Zhou, Anurag Arnab, Cordelia Schmid Domain Adaptive Imitation Learning with Visual Observation
Sungho Choi, Seungyul Han, Woojun Kim, Jongseong Chae, Whiyoung Jung, Youngchul Sung Domain Re-Modulation for Few-Shot Generative Domain Adaptation
Yi Wu, Ziqiang Li, Chaoyue Wang, Heliang Zheng, Shanshan Zhao, Bin Li, Dacheng Tao DoReMi: Optimizing Data Mixtures Speeds up Language Model Pretraining
Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V Le, Tengyu Ma, Adams Wei Yu Double Gumbel Q-Learning
David Yu-Tung Hui, Aaron C. Courville, Pierre-Luc Bacon Doubly Constrained Fair Clustering
John Dickerson, Seyed Esmaeili, Jamie H Morgenstern, Claire Jie Zhang Doubly Robust Augmented Transfer for Meta-Reinforcement Learning
Yuankun Jiang, Nuowen Kan, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong Doubly-Robust Self-Training
Banghua Zhu, Mingyu Ding, Philip Jacobson, Ming Wu, Wei Zhan, Michael I. Jordan, Jiantao Jiao DP-Mix: Mixup-Based Data Augmentation for Differentially Private Learning
Wenxuan Bao, Francesco Pittaluga, B G Vijay Kumar, Vincent Bindschaedler DPOK: Reinforcement Learning for Fine-Tuning Text-to-Image Diffusion Models
Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee DreamHuman: Animatable 3D Avatars from Text
Nikos Kolotouros, Thiemo Alldieck, Andrei Zanfir, Eduard Bazavan, Mihai Fieraru, Cristian Sminchisescu DreamSim: Learning New Dimensions of Human Visual Similarity Using Synthetic Data
Stephanie Fu, Netanel Tamir, Shobhita Sundaram, Lucy Chai, Richard Zhang, Tali Dekel, Phillip Isola DreamWaltz: Make a Scene with Complex 3D Animatable Avatars
Yukun Huang, Jianan Wang, Ailing Zeng, He Cao, Xianbiao Qi, Yukai Shi, Zheng-Jun Zha, Lei Zhang DropCompute: Simple and More Robust Distributed Synchronous Training via Compute Variance Reduction
Niv Giladi, Shahar Gottlieb, Moran Shkolnik, Asaf Karnieli, Ron Banner, Elad Hoffer, Kfir Y. Levy, Daniel Soudry DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions
Haochen Wang, Junsong Fan, Yuxi Wang, Kaiyou Song, Tong Wang, Zhao-Xiang Zhang DrugCLIP: Contrastive Protein-Molecule Representation Learning for Virtual Screening
Bowen Gao, Bo Qiang, Haichuan Tan, Yinjun Jia, Minsi Ren, Minsi Lu, Jingjing Liu, Wei-Ying Ma, Yanyan Lan DVSOD: RGB-D Video Salient Object Detection
Jingjing Li, Wei Ji, Size Wang, Wenbo Li, Li Cheng Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers
Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurelien Lucchi, Thomas Hofmann Dynamic Non-Monotone Submodular Maximization
Kiarash Banihashem, Leyla Biabani, Samira Goudarzi, MohammadTaghi Hajiaghayi, Peyman Jabbarzade, Morteza Monemizadeh Dynamic Sparsity Is Channel-Level Sparsity Learner
Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang "Atlas" Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu Dynamically Masked Discriminator for GANs
Wentian Zhang, Haozhe Liu, Bing Li, Jinheng Xie, Yawen Huang, Yuexiang Li, Yefeng Zheng, Bernard Ghanem DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets
Lazar Atanackovic, Alexander Tong, Bo Wang, Leo J Lee, Yoshua Bengio, Jason S Hartford DynPoint: Dynamic Neural Point for View Synthesis
Kaichen Zhou, Jia-Xing Zhong, Sangyun Shin, Kai Lu, Yiyuan Yang, Andrew Markham, Niki Trigoni E2PNet: Event to Point Cloud Registration with Spatio-Temporal Representation Learning
Xiuhong Lin, Changjie Qiu, Zhipeng Cai, Siqi Shen, Yu Zang, Weiquan Liu, Xuesheng Bian, Matthias Müller, Cheng Wang Easy Learning from Label Proportions
Róbert Busa-Fekete, Heejin Choi, Travis Dick, Claudio Gentile, Andres Munoz Medina Ecosystem-Level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes
Connor Toups, Rishi Bommasani, Kathleen Creel, Sarah Bana, Dan Jurafsky, Percy Liang Effective Human-AI Teams via Learned Natural Language Rules and Onboarding
Hussein Mozannar, Jimin Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David Sontag Effective Robustness Against Natural Distribution Shifts for Models with Different Training Data
Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning
Akhil Bagaria, Ben Abbatematteo, Omer Gottesman, Matt Corsaro, Sreehari Rammohan, George Konidaris Efficient Beam Tree Recursion
Jishnu Ray Chowdhury, Cornelia Caragea Efficient Equivariant Transfer Learning from Pretrained Models
Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Driggs-Campbell, Payel Das, Lav R. Varshney Efficient Exploration in Continuous-Time Model-Based Reinforcement Learning
Lenart Treven, Jonas Hübotter, Bhavya Sukhija, Florian Dorfler, Andreas Krause Efficient Hyper-Parameter Optimization with Cubic Regularization
Zhenqian Shen, Hansi Yang, Yong Li, James T. Kwok, Quanming Yao Efficient Low-Rank Backpropagation for Vision Transformer Adaptation
Yuedong Yang, Hung-Yueh Chiang, Guihong Li, Diana Marculescu, Radu Marculescu Efficient Model-Free Exploration in Low-Rank MDPs
Zak Mhammedi, Adam Block, Dylan J Foster, Alexander Rakhlin Efficient Neural Music Generation
Max W. Y. Lam, Qiao Tian, Tang Li, Zongyu Yin, Siyuan Feng, Ming Tu, Yuliang Ji, Rui Xia, Mingbo Ma, Xuchen Song, Jitong Chen, Wang Yuping, Yuxuan Wang Efficient Online Clustering with Moving Costs
Dimitrios Christou, Stratis Skoulakis, Volkan Cevher Efficient Subgame Refinement for Extensive-Form Games
Zhenxing Ge, Zheng Xu, Tianyu Ding, Wenbin Li, Yang Gao Efficient Symbolic Policy Learning with Differentiable Symbolic Expression
Jiaming Guo, Rui Zhang, Shaohui Peng, Qi Yi, Xing Hu, Ruizhi Chen, Zidong Du, Xishan Zhang, Ling Li, Qi Guo, Yunji Chen Efficient Testable Learning of Halfspaces with Adversarial Label Noise
Ilias Diakonikolas, Daniel Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis Ego4D Goal-Step: Toward Hierarchical Understanding of Procedural Activities
Yale Song, Eugene Byrne, Tushar Nagarajan, Huiyu Wang, Miguel Martin, Lorenzo Torresani EgoEnv: Human-Centric Environment Representations from Egocentric Video
Tushar Nagarajan, Santhosh Kumar Ramakrishnan, Ruta Desai, James Hillis, Kristen Grauman EgoTracks: A Long-Term Egocentric Visual Object Tracking Dataset
Hao Tang, Kevin J Liang, Kristen Grauman, Matt Feiszli, Weiyao Wang EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
Michael Wornow, Rahul Thapa, Ethan Steinberg, Jason Fries, Nigam Shah EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-Ray Images
Seongsu Bae, Daeun Kyung, Jaehee Ryu, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei Ji, Eric I. Chang, Tackeun Kim, Edward Choi Elastic Decision Transformer
Yueh-Hua Wu, Xiaolong Wang, Masashi Hamaya ELDEN: Exploration via Local Dependencies
Zizhao Wang, Jiaheng Hu, Peter Stone, Roberto Martín-Martín Eliminating Domain Bias for Federated Learning in Representation Space
Jianqing Zhang, Yang Hua, Jian Cao, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan EmbodiedGPT: Vision-Language Pre-Training via Embodied Chain of Thought
Yao Mu, Qinglong Zhang, Mengkang Hu, Wenhai Wang, Mingyu Ding, Jun Jin, Bin Wang, Jifeng Dai, Yu Qiao, Ping Luo Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
Neel Guha, Mayee Chen, Kush Bhatia, Azalia Mirhoseini, Frederic Sala, Christopher Ré Emergent and Predictable Memorization in Large Language Models
Stella Biderman, Usvsn Prashanth, Lintang Sutawika, Hailey Schoelkopf, Quentin Anthony, Shivanshu Purohit, Edward Raff Emergent Communication for Rules Reasoning
Yuxuan Guo, Yifan Hao, Rui Zhang, Enshuai Zhou, Zidong Du, Xishan Zhang, Xinkai Song, Yuanbo Wen, Yongwei Zhao, Xuehai Zhou, Jiaming Guo, Qi Yi, Shaohui Peng, Di Huang, Ruizhi Chen, Qi Guo, Yunji Chen Emergent Correspondence from Image Diffusion
Luming Tang, Menglin Jia, Qianqian Wang, Cheng Perng Phoo, Bharath Hariharan Empowering Convolutional Neural Nets with MetaSin Activation
Farnood Salehi, Tunç Aydin, André Gaillard, Guglielmo Camporese, Yuxuan Wang Encoding Time-Series Explanations Through Self-Supervised Model Behavior Consistency
Owen Queen, Tom Hartvigsen, Teddy Koker, Huan He, Theodoros Tsiligkaridis, Marinka Zitnik End-to-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics
Alexander Shmakov, Kevin Greif, Michael Fenton, Aishik Ghosh, Pierre Baldi, Daniel Whiteson End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes
Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Haitham Bou Ammar Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
Tobias Schröder, Zijing Ou, Jen Lim, Yingzhen Li, Sebastian Vollmer, Andrew Duncan Energy Guided Diffusion for Generating Neurally Exciting Images
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Benjamin Hoover, Yuchen Liang, Bao Pham, Rameswar Panda, Hendrik Strobelt, Duen Horng Chau, Mohammed Zaki, Dmitry Krotov Energy-Efficient Scheduling with Predictions
Eric Balkanski, Noemie Perivier, Clifford Stein, Hao-Ting Wei Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns
Xin Liu, Zheng Li, Yifan Gao, Jingfeng Yang, Tianyu Cao, Zhengyang Wang, Bing Yin, Yangqiu Song Entropic Neural Optimal Transport via Diffusion Processes
Nikita Gushchin, Alexander Kolesov, Alexander Korotin, Dmitry P Vetrov, Evgeny Burnaev Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization
Haonan Yuan, Qingyun Sun, Xingcheng Fu, Ziwei Zhang, Cheng Ji, Hao Peng, Jianxin Li EPIC Fields: Marrying 3D Geometry and Video Understanding
Vadim Tschernezki, Ahmad Darkhalil, Zhifan Zhu, David Fouhey, Iro Laina, Diane Larlus, Dima Damen, Andrea Vedaldi Epidemic Learning: Boosting Decentralized Learning with Randomized Communication
Martijn De Vos, Sadegh Farhadkhani, Rachid Guerraoui, Anne-marie Kermarrec, Rafael Pires, Rishi Sharma Epistemic Neural Networks
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy Equal Opportunity of Coverage in Fair Regression
Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S Yu Equivariant Adaptation of Large Pretrained Models
Arnab Kumar Mondal, Siba Smarak Panigrahi, Oumar Kaba, Sai Rajeswar Mudumba, Siamak Ravanbakhsh Equivariant Flow Matching
Leon Klein, Andreas Krämer, Frank Noe Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation
Yuxuan Song, Jingjing Gong, Minkai Xu, Ziyao Cao, Yanyan Lan, Stefano Ermon, Hao Zhou, Wei-Ying Ma Error Discovery by Clustering Influence Embeddings
Fulton Wang, Julius Adebayo, Sarah Tan, Diego Garcia-Olano, Narine Kokhlikyan Ess-InfoGAIL: Semi-Supervised Imitation Learning from Imbalanced Demonstrations
Huiqiao Fu, Kaiqiang Tang, Yuanyang Lu, Yiming Qi, Guizhou Deng, Flood Sung, Chunlin Chen Estimating Generic 3D Room Structures from 2D Annotations
Denys Rozumnyi, Stefan Popov, Kevis-kokitsi Maninis, Matthias Niessner, Vittorio Ferrari Estimating Koopman Operators with Sketching to Provably Learn Large Scale Dynamical Systems
Giacomo Meanti, Antoine Chatalic, Vladimir Kostic, Pietro Novelli, Massimiliano Pontil, Lorenzo Rosasco Ethical Considerations for Responsible Data Curation
Jerone Andrews, Dora Zhao, William Thong, Apostolos Modas, Orestis Papakyriakopoulos, Alice Xiang EV-Eye: Rethinking High-Frequency Eye Tracking Through the Lenses of Event Cameras
Guangrong Zhao, Yurun Yang, Jingwei Liu, Ning Chen, Yiran Shen, Hongkai Wen, Guohao Lan Evaluating and Improving Tool-Augmented Computation-Intensive Math Reasoning
Beichen Zhang, Kun Zhou, Xilin Wei, Xin Zhao, Jing Sha, Shijin Wang, Ji-Rong Wen Evaluating and Inducing Personality in Pre-Trained Language Models
Guangyuan Jiang, Manjie Xu, Song-Chun Zhu, Wenjuan Han, Chi Zhang, Yixin Zhu Evaluating Cognitive Maps and Planning in Large Language Models with CogEval
Ida Momennejad, Hosein Hasanbeig, Felipe Vieira Frujeri, Hiteshi Sharma, Nebojsa Jojic, Hamid Palangi, Robert Ness, Jonathan Larson Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin Evaluating Open-QA Evaluation
Cunxiang Wang, Sirui Cheng, Qipeng Guo, Yuanhao Yue, Bowen Ding, Zhikun Xu, Yidong Wang, Xiangkun Hu, Zheng Zhang, Yue Zhang Evaluating Self-Supervised Learning for Molecular Graph Embeddings
Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu Evaluating the Moral Beliefs Encoded in LLMs
Nino Scherrer, Claudia Shi, Amir Feder, David M. Blei EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning
Mohammad Mahdi Rahimi, Hasnain Irshad Bhatti, Younghyun Park, Humaira Kousar, Jaekyun Moon Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing
Shangshang Yang, Xiaoshan Yu, Ye Tian, Xueming Yan, Haiping Ma, Xingyi Zhang Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings
Sudhanshu Chanpuriya, Ryan Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Zhao Song, Cameron Musco Exact Verification of ReLU Neural Control Barrier Functions
Hongchao Zhang, Junlin Wu, Yevgeniy Vorobeychik, Andrew Clark Expanding Small-Scale Datasets with Guided Imagination
Yifan Zhang, Daquan Zhou, Bryan Hooi, Kai Wang, Jiashi Feng Experimental Designs for Heteroskedastic Variance
Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain Explainable and Efficient Randomized Voting Rules
Soroush Ebadian, Aris Filos-Ratsikas, Mohamad Latifian, Nisarg Shah Explainable Brain Age Prediction Using coVariance Neural Networks
Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro Exploiting Contextual Objects and Relations for 3D Visual Grounding
Li Yang, Chunfeng Yuan, Ziqi Zhang, Zhongang Qi, Yan Xu, Wei Liu, Ying Shan, Bing Li, Weiping Yang, Peng Li, Yan Wang, Weiming Hu Exploiting Hidden Structures in Non-Convex Games for Convergence to Nash Equilibrium
Iosif Sakos, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Panayotis Mertikopoulos, Georgios Piliouras Explore In-Context Learning for 3D Point Cloud Understanding
Zhongbin Fang, Xiangtai Li, Xia Li, Joachim M Buhmann, Chen Change Loy, Mengyuan Liu Explore to Generalize in Zero-Shot RL
Ev Zisselman, Itai Lavie, Daniel Soudry, Aviv Tamar Exploring Geometry of Blind Spots in Vision Models
Sriram Balasubramanian, Gaurang Sriramanan, Vinu Sankar Sadasivan, Soheil Feizi Exploring Question Decomposition for Zero-Shot VQA
Zaid Khan, B G Vijay Kumar, Samuel Schulter, Manmohan Chandraker, Yun Fu Exponential Lower Bounds for Fictitious Play in Potential Games
Ioannis Panageas, Nikolas Patris, Stratis Skoulakis, Volkan Cevher Exposing Attention Glitches with Flip-Flop Language Modeling
Bingbin Liu, Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang Exposing Flaws of Generative Model Evaluation Metrics and Their Unfair Treatment of Diffusion Models
George Stein, Jesse Cresswell, Rasa Hosseinzadeh, Yi Sui, Brendan Ross, Valentin Villecroze, Zhaoyan Liu, Anthony L Caterini, Eric Taylor, Gabriel Loaiza-Ganem Expressivity-Preserving GNN Simulation
Fabian Jogl, Maximilian Thiessen, Thomas Gärtner Extensible Prompts for Language Models on Zero-Shot Language Style Customization
Tao Ge, Hu Jing, Li Dong, Shaoguang Mao, Yan Xia, Xun Wang, Si-Qing Chen, Furu Wei Extremal Domain Translation with Neural Optimal Transport
Milena Gazdieva, Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev FABind: Fast and Accurate Protein-Ligand Binding
Qizhi Pei, Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Kun He, Tie-Yan Liu, Rui Yan FaceComposer: A Unified Model for Versatile Facial Content Creation
Jiayu Wang, Kang Zhao, Yifeng Ma, Shiwei Zhang, Yingya Zhang, Yujun Shen, Deli Zhao, Jingren Zhou Factorized Contrastive Learning: Going Beyond Multi-View Redundancy
Paul Pu Liang, Zihao Deng, Martin Q. Ma, James Y Zou, Louis-Philippe Morency, Ruslan Salakhutdinov Fair Adaptive Experiments
Waverly Wei, Xinwei Ma, Jingshen Wang Fair Canonical Correlation Analysis
Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Boning Tong, Jia Xu, Yanbo Feng, Qi Long, Li Shen Fair Graph Distillation
Qizhang Feng, Zhimeng Jiang, Ruiquan Li, Yicheng Wang, Na Zou, Jiang Bian, Xia Hu Fair, Polylog-Approximate Low-Cost Hierarchical Clustering
Marina Knittel, Max Springer, John Dickerson, MohammadTaghi Hajiaghayi FairLISA: Fair User Modeling with Limited Sensitive Attributes Information
Zheng Zhang, Qi Liu, Hao Jiang, Fei Wang, Yan Zhuang, Le Wu, Weibo Gao, Enhong Chen Fairness Aware Counterfactuals for Subgroups
Loukas Kavouras, Konstantinos Tsopelas, Giorgos Giannopoulos, Dimitris Sacharidis, Eleni Psaroudaki, Nikolaos Theologitis, Dimitrios Rontogiannis, Dimitris Fotakis, Ioannis Emiris Fairness-Guided Few-Shot Prompting for Large Language Models
Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu Faith and Fate: Limits of Transformers on Compositionality
Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Li, Liwei Jiang, Bill Yuchen Lin, Sean Welleck, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena Hwang, Soumya Sanyal, Xiang Ren, Allyson Ettinger, Zaid Harchaoui, Yejin Choi False Discovery Proportion Control for Aggregated Knockoffs
Alexandre Blain, Bertrand Thirion, Olivier Grisel, Pierre Neuvial FAMO: Fast Adaptive Multitask Optimization
Bo Liu, Yihao Feng, Peter Stone, Qiang Liu Fast Model DeBias with Machine Unlearning
Ruizhe Chen, Jianfei Yang, Huimin Xiong, Jianhong Bai, Tianxiang Hu, Jin Hao, Yang Feng, Joey Tianyi Zhou, Jian Wu, Zuozhu Liu Fast Optimal Locally Private Mean Estimation via Random Projections
Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy Nguyen, Kunal Talwar Fast Optimal Transport Through Sliced Generalized Wasserstein Geodesics
Guillaume Mahey, Laetitia Chapel, Gilles Gasso, Clément Bonet, Nicolas Courty Fast Trainable Projection for Robust Fine-Tuning
Junjiao Tian, Yen-Cheng Liu, James S Smith, Zsolt Kira Faster Approximate Subgraph Counts with Privacy
Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan, Anil Vullikanti Faster Relative Entropy Coding with Greedy Rejection Coding
Gergely Flamich, Stratis Markou, José Miguel Hernández-Lobato Feature Adaptation for Sparse Linear Regression
Jonathan Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi Feature-Learning Networks Are Consistent Across Widths at Realistic Scales
Nikhil Vyas, Alexander Atanasov, Blake Bordelon, Depen Morwani, Sabarish Sainathan, Cengiz Pehlevan Fed-GraB: Federated Long-Tailed Learning with Self-Adjusting Gradient Balancer
Zikai Xiao, Zihan Chen, Songshang Liu, Hualiang Wang, Yang Feng, Jin Hao, Joey Tianyi Zhou, Jian Wu, Howard Hua Yang, Zuozhu Liu Federated Compositional Deep AUC Maximization
Xinwen Zhang, Yihan Zhang, Tianbao Yang, Richard Souvenir, Hongchang Gao Federated Conditional Stochastic Optimization
Xidong Wu, Jianhui Sun, Zhengmian Hu, Junyi Li, Aidong Zhang, Heng Huang Federated Learning via Meta-Variational Dropout
Insu Jeon, Minui Hong, Junhyeog Yun, Gunhee Kim Federated Multi-Objective Learning
Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma FedFed: Feature Distillation Against Data Heterogeneity in Federated Learning
Zhiqin Yang, Yonggang Zhang, Yu Zheng, Xinmei Tian, Hao Peng, Tongliang Liu, Bo Han FedGame: A Game-Theoretic Defense Against Backdoor Attacks in Federated Learning
Jinyuan Jia, Zhuowen Yuan, Dinuka Sahabandu, Luyao Niu, Arezoo Rajabi, Bhaskar Ramasubramanian, Bo Li, Radha Poovendran FedL2P: Federated Learning to Personalize
Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy Hospedales, Ferenc Huszar, Nicholas Lane FELM: Benchmarking Factuality Evaluation of Large Language Models
Shiqi Chen, Yiran Zhao, Jinghan Zhang, I-Chun Chern, Siyang Gao, Pengfei Liu, Junxian He FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation
Yuanxin Liu, Lei Li, Shuhuai Ren, Rundong Gao, Shicheng Li, Sishuo Chen, Xu Sun, Lu Hou FGPrompt: Fine-Grained Goal Prompting for Image-Goal Navigation
Xinyu Sun, Peihao Chen, Jugang Fan, Jian Chen, Thomas Li, Mingkui Tan FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations
Chanakya Ekbote, Ajinkya Deshpande, Arun Iyer, Sundararajan Sellamanickam, Ramakrishna Bairi FIND: A Function Description Benchmark for Evaluating Interpretability Methods
Sarah Schwettmann, Tamar Shaham, Joanna Materzynska, Neil Chowdhury, Shuang Li, Jacob Andreas, David Bau, Antonio Torralba Fine-Grained Expressivity of Graph Neural Networks
Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
Zeqiu Wu, Yushi Hu, Weijia Shi, Nouha Dziri, Alane Suhr, Prithviraj Ammanabrolu, Noah A. Smith, Mari Ostendorf, Hannaneh Hajishirzi Fine-Grained Visual Prompting
Lingfeng Yang, Yueze Wang, Xiang Li, Xinlong Wang, Jian Yang Fine-Tuning Language Models with Just Forward Passes
Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason Lee, Danqi Chen, Sanjeev Arora FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing
Mingyuan Zhang, Huirong Li, Zhongang Cai, Jiawei Ren, Lei Yang, Ziwei Liu Finite-Time Logarithmic Bayes Regret Upper Bounds
Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi First Order Methods with Markovian Noise: From Acceleration to Variational Inequalities
Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander Gasnikov, Alexey Naumov, Eric Moulines First Order Stochastic Optimization with Oblivious Noise
Ilias Diakonikolas, Sushrut Karmalkar, Jong Ho Park, Christos Tzamos FLAIR : A Country-Scale Land Cover Semantic Segmentation Dataset from Multi-Source Optical Imagery
Anatol Garioud, Nicolas Gonthier, Loic Landrieu, Apolline De Wit, Marion Valette, Marc Poupée, Sebastien Giordano, Boris Wattrelos Flat Seeking Bayesian Neural Networks
Van-Anh Nguyen, Tung-Long Vuong, Hoang Phan, Thanh-Toan Do, Dinh Phung, Trung Le Flow Factorized Representation Learning
Yue Song, Andy Keller, Nicu Sebe, Max Welling Flow Matching for Scalable Simulation-Based Inference
Jonas Wildberger, Maximilian Dax, Simon Buchholz, Stephen Green, Jakob H Macke, Bernhard Schölkopf Flow: Per-Instance Personalized Federated Learning
Kunjal Panchal, Sunav Choudhary, Nisarg Parikh, Lijun Zhang, Hui Guan FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space
Shengzhong Liu, Tomoyoshi Kimura, Dongxin Liu, Ruijie Wang, Jinyang Li, Suhas Diggavi, Mani Srivastava, Tarek Abdelzaher Focused Transformer: Contrastive Training for Context Scaling
Szymon Tworkowski, Konrad Staniszewski, Mikołaj Pacek, Yuhuai Wu, Henryk Michalewski, Piotr Miłoś Follow-Ups Also Matter: Improving Contextual Bandits via Post-Serving Contexts
Chaoqi Wang, Ziyu Ye, Zhe Feng, Ashwinkumar Badanidiyuru Varadaraja, Haifeng Xu For SALE: State-Action Representation Learning for Deep Reinforcement Learning
Scott Fujimoto, Wei-Di Chang, Edward Smith, Shixiang Gu, Doina Precup, David Meger ForecastPFN: Synthetically-Trained Zero-Shot Forecasting
Samuel Dooley, Gurnoor Singh Khurana, Chirag Mohapatra, Siddartha V Naidu, Colin White ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning
Junguang Jiang, Baixu Chen, Junwei Pan, Ximei Wang, Dapeng Liu, Jie Jiang, Mingsheng Long Formalizing Locality for Normative Synaptic Plasticity Models
Colin Bredenberg, Ezekiel Williams, Cristina Savin, Blake Richards, Guillaume Lajoie Foundation Model Is Efficient Multimodal Multitask Model Selector
Fanqing Meng, Wenqi Shao, Zhanglin Peng, Chonghe Jiang, Kaipeng Zhang, Yu Qiao, Ping Luo FouriDown: Factoring Down-Sampling into Shuffling and Superposing
Qi Zhu, Man Zhou, Jie Huang, Naishan Zheng, Hongzhi Gao, Chongyi Li, Yuan Xu, Feng Zhao FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective
Kun Yi, Qi Zhang, Wei Fan, Hui He, Liang Hu, Pengyang Wang, Ning An, Longbing Cao, Zhendong Niu Frequency Domain-Based Dataset Distillation
Donghyeok Shin, Seungjae Shin, Il-chul Moon Frequency-Domain MLPs Are More Effective Learners in Time Series Forecasting
Kun Yi, Qi Zhang, Wei Fan, Shoujin Wang, Pengyang Wang, Hui He, Ning An, Defu Lian, Longbing Cao, Zhendong Niu From Discrete Tokens to High-Fidelity Audio Using Multi-Band Diffusion
Robin San Roman, Yossi Adi, Antoine Deleforge, Romain Serizel, Gabriel Synnaeve, Alexandre Defossez From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces
Peter Shaw, Mandar Joshi, James Cohan, Jonathan Berant, Panupong Pasupat, Hexiang Hu, Urvashi Khandelwal, Kenton Lee, Kristina N Toutanova From Trainable Negative Depth to Edge Heterophily in Graphs
Yuchen Yan, Yuzhong Chen, Huiyuan Chen, Minghua Xu, Mahashweta Das, Hao Yang, Hanghang Tong Full-Atom Protein Pocket Design via Iterative Refinement
Zaixi Zhang, Zepu Lu, Hao Zhongkai, Marinka Zitnik, Qi Liu Fully Dynamic $k$-Clustering in $\tilde O(k)$ Update Time
Sayan Bhattacharya, Martín Costa, Silvio Lattanzi, Nikos Parotsidis Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration
Haitao Lin, Yufei Huang, Odin Zhang, Yunfan Liu, Lirong Wu, Siyuan Li, Zhiyuan Chen, Stan Z. Li Fused Gromov-Wasserstein Graph Mixup for Graph-Level Classifications
Xinyu Ma, Xu Chu, Yasha Wang, Yang Lin, Junfeng Zhao, Liantao Ma, Wenwu Zhu Future-Dependent Value-Based Off-Policy Evaluation in POMDPs
Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun Gacs-Korner Common Information Variational Autoencoder
Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan Kao Game Solving with Online Fine-Tuning
Ti-Rong Wu, Hung Guei, Ting Han Wei, Chung-Chin Shih, Jui-Te Chin, I-Chen Wu GAN You See Me? Enhanced Data Reconstruction Attacks Against Split Inference
Ziang Li, Mengda Yang, Yaxin Liu, Juan Wang, Hongxin Hu, Wenzhe Yi, Xiaoyang Xu GAUCHE: A Library for Gaussian Processes in Chemistry
Ryan-Rhys Griffiths, Leo Klarner, Henry Moss, Aditya Ravuri, Sang Truong, Yuanqi Du, Samuel Stanton, Gary Tom, Bojana Rankovic, Arian Jamasb, Aryan Deshwal, Julius Schwartz, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Johannes Peter Dürholt, Saudamini Chaurasia, Ji Won Park, Felix Strieth-Kalthoff, Alpha Lee, Bingqing Cheng, Alan Aspuru-Guzik, Philippe Schwaller, Jian Tang Gaussian Differential Privacy on Riemannian Manifolds
Yangdi Jiang, Xiaotian Chang, Yi Liu, Lei Ding, Linglong Kong, Bei Jiang Gaussian Membership Inference Privacy
Tobias Leemann, Martin Pawelczyk, Gjergji Kasneci Gaussian Mixture Solvers for Diffusion Models
Hanzhong Guo, Cheng Lu, Fan Bao, Tianyu Pang, Shuicheng Yan, Chao Du, Chongxuan Li Gaussian Partial Information Decomposition: Bias Correction and Application to High-Dimensional Data
Praveen Venkatesh, Corbett Bennett, Sam Gale, Tamina Ramirez, Greggory Heller, Severine Durand, Shawn Olsen, Stefan Mihalas Gaussian Process Probes (GPP) for Uncertainty-Aware Probing
Zi Wang, Alexander Ku, Jason Baldridge, Tom Griffiths, Been Kim Generalizable One-Shot 3D Neural Head Avatar
Xueting Li, Shalini De Mello, Sifei Liu, Koki Nagano, Umar Iqbal, Jan Kautz Generalized Belief Transport
Junqi Wang, Pei Wang, Patrick Shafto Generalized Semi-Supervised Learning via Self-Supervised Feature Adaptation
Jiachen Liang, RuiBing Hou, Hong Chang, Bingpeng Ma, Shiguang Shan, Xilin Chen Generalized Test Utilities for Long-Tail Performance in Extreme Multi-Label Classification
Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, Krzysztof J. Dembczynski Generating QM1B with PySCF$_{\text{IPU}}$
Alexander Mathiasen, Hatem Helal, Kerstin Klaser, Paul Balanca, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew W. Fitzgibbon, Dominic Masters GenImage: A Million-Scale Benchmark for Detecting AI-Generated Image
Mingjian Zhu, Hanting Chen, Qiangyu Yan, Xudong Huang, Guanyu Lin, Wei Li, Zhijun Tu, Hailin Hu, Jie Hu, Yunhe Wang GenS: Generalizable Neural Surface Reconstruction from Multi-View Images
Rui Peng, Xiaodong Gu, Luyang Tang, Shihe Shen, Fanqi Yu, Ronggang Wang GEO-Bench: Toward Foundation Models for Earth Monitoring
Alexandre Lacoste, Nils Lehmann, Pau Rodriguez, Evan Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vazquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu GeoDE: A Geographically Diverse Evaluation Dataset for Object Recognition
Vikram V. Ramaswamy, Sing Yu Lin, Dora Zhao, Aaron Adcock, Laurens van der Maaten, Deepti Ghadiyaram, Olga Russakovsky Geodesic Multi-Modal Mixup for Robust Fine-Tuning
Changdae Oh, Junhyuk So, Hoyoon Byun, YongTaek Lim, Minchul Shin, Jong-June Jeon, Kyungwoo Song Geometric Algebra Transformer
Johann Brehmer, Pim de Haan, Sönke Behrends, Taco S Cohen Geometric Neural Diffusion Processes
Emile Mathieu, Vincent Dutordoir, Michael Hutchinson, Valentin De Bortoli, Yee Whye Teh, Richard Turner Geometric Transformer with Interatomic Positional Encoding
Yusong Wang, Shaoning Li, Tong Wang, Bin Shao, Nanning Zheng, Tie-Yan Liu Geometry-Aware Adaptation for Pretrained Models
Nicholas Roberts, Xintong Li, Dyah Adila, Sonia Cromp, Tzu-Heng Huang, Jitian Zhao, Frederic Sala Geometry-Informed Neural Operator for Large-Scale 3D PDEs
Zongyi Li, Nikola Kovachki, Chris Choy, Boyi Li, Jean Kossaifi, Shourya Otta, Mohammad Amin Nabian, Maximilian Stadler, Christian Hundt, Kamyar Azizzadenesheli, Animashree Anandkumar Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design
Ibrahim M Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer Gigastep - One Billion Steps per Second Multi-Agent Reinforcement Learning
Mathias Lechner, Lianhao Yin, Tim Seyde, Tsun-Hsuan Johnson Wang, Wei Xiao, Ramin Hasani, Joshua Rountree, Daniela Rus GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning
Haiteng Zhao, Shengchao Liu, Ma Chang, Hannan Xu, Jie Fu, Zhihong Deng, Lingpeng Kong, Qi Liu GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection
Namyong Park, Ryan Rossi, Xing Wang, Antoine Simoulin, Nesreen K. Ahmed, Christos Faloutsos Global Optimality in Bivariate Gradient-Based DAG Learning
Chang Deng, Kevin Bello, Pradeep K. Ravikumar, Bryon Aragam Globally Injective and Bijective Neural Operators
Takashi Furuya, Michael Puthawala, Matti Lassas, Maarten V. de Hoop GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David Evans GlyphControl: Glyph Conditional Control for Visual Text Generation
Yukang Yang, Dongnan Gui, Yuhui Yuan, Weicong Liang, Haisong Ding, Han Hu, Kai Chen GMSF: Global Matching Scene Flow
Yushan Zhang, Johan Edstedt, Bastian Wandt, Per-Erik Forssen, Maria Magnusson, Michael Felsberg GNeSF: Generalizable Neural Semantic Fields
Hanlin Chen, Chen Li, Mengqi Guo, Zhiwen Yan, Gim Hee Lee GNNEvaluator: Evaluating GNN Performance on Unseen Graphs Without Labels
Xin Zheng, Miao Zhang, Chunyang Chen, Soheila Molaei, Chuan Zhou, Shirui Pan Gold-YOLO: Efficient Object Detector via Gather-and-Distribute Mechanism
Chengcheng Wang, Wei He, Ying Nie, Jianyuan Guo, Chuanjian Liu, Yunhe Wang, Kai Han GPEX, a Framework for Interpreting Artificial Neural Networks
Amir Hossein Hosseini Akbarnejad, Gilbert Bigras, Nilanjan Ray Gradient Informed Proximal Policy Optimization
Sanghyun Son, Laura Zheng, Ryan Sullivan, Yi-Ling Qiao, Ming Lin Gradient-Based Feature Learning Under Structured Data
Alireza Mousavi-Hosseini, Denny Wu, Taiji Suzuki, Murat A Erdogdu Graph Denoising Diffusion for Inverse Protein Folding
Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Lió, Yuguang Wang Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling
Haotao Wang, Ziyu Jiang, Yuning You, Yan Han, Gaowen Liu, Jayanth Srinivasa, Ramana Kompella, Zhangyang "Atlas" Wang Graph of Circuits with GNN for Exploring the Optimal Design Space
Aditya Shahane, Saripilli Swapna Manjiri, Ankesh Jain, Sandeep Kumar GraphAdapter: Tuning Vision-Language Models with Dual Knowledge Graph
Xin Li, Dongze Lian, Zhihe Lu, Jiawang Bai, Zhibo Chen, Xinchao Wang Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents
Wenlong Huang, Fei Xia, Dhruv Shah, Danny Driess, Andy Zeng, Yao Lu, Pete Florence, Igor Mordatch, Sergey Levine, Karol Hausman, Brian Ichter Grounding Neural Inference with Satisfiability Modulo Theories
Zifan Wang, Saranya Vijayakumar, Kaiji Lu, Vijay Ganesh, Somesh Jha, Matt Fredrikson Group Fairness in Peer Review
Haris Aziz, Evi Micha, Nisarg Shah Group Robust Classification Without Any Group Information
Christos Tsirigotis, Joao Monteiro, Pau Rodriguez, David Vazquez, Aaron C. Courville GSLB: The Graph Structure Learning Benchmark
Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Yu Guide Your Agent with Adaptive Multimodal Rewards
Changyeon Kim, Younggyo Seo, Hao Liu, Lisa Lee, Jinwoo Shin, Honglak Lee, Kimin Lee Guiding Large Language Models via Directional Stimulus Prompting
Zekun Li, Baolin Peng, Pengcheng He, Michel Galley, Jianfeng Gao, Xifeng Yan Guiding the Last Layer in Federated Learning with Pre-Trained Models
Gwen Legate, Nicolas Bernier, Lucas Page-Caccia, Edouard Oyallon, Eugene Belilovsky H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models
Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark Barrett, Zhangyang "Atlas" Wang, Beidi Chen HAP: Structure-Aware Masked Image Modeling for Human-Centric Perception
Junkun Yuan, Xinyu Zhang, Hao Zhou, Jian Wang, Zhongwei Qiu, Zhiyin Shao, Shaofeng Zhang, Sifan Long, Kun Kuang, Kun Yao, Junyu Han, Errui Ding, Lanfen Lin, Fei Wu, Jingdong Wang Hardware Resilience Properties of Text-Guided Image Classifiers
Syed Talal Wasim, Kabila Haile Soboka, Abdulrahman Mahmoud, Salman H Khan, David Brooks, Gu-Yeon Wei Harnessing Hard Mixed Samples with Decoupled Regularizer
Zicheng Liu, Siyuan Li, Ge Wang, Lirong Wu, Cheng Tan, Stan Z. Li Harnessing the Power of Choices in Decision Tree Learning
Guy Blanc, Jane Lange, Chirag Pabbaraju, Colin Sullivan, Li-Yang Tan, Mo Tiwari Have It Your Way: Individualized Privacy Assignment for DP-SGD
Franziska Boenisch, Christopher Mühl, Adam Dziedzic, Roy Rinberg, Nicolas Papernot HeadSculpt: Crafting 3D Head Avatars with Text
Xiao Han, Yukang Cao, Kai Han, Xiatian Zhu, Jiankang Deng, Yi-Zhe Song, Tao Xiang, Kwan-Yee K. Wong Hierarchical Gaussian Mixture Based Task Generative Model for Robust Meta-Learning
Yizhou Zhang, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Liang Tong, Haifeng Chen, Yan Liu Hierarchical Integration Diffusion Model for Realistic Image Deblurring
Zheng Chen, Yulun Zhang, Ding Liu, Bin Xia, Jinjin Gu, Linghe Kong, Xin Yuan Hierarchical Multi-Agent Skill Discovery
Mingyu Yang, Yaodong Yang, Zhenbo Lu, Wengang Zhou, Houqiang Li Hierarchical Open-Vocabulary Universal Image Segmentation
Xudong Wang, Shufan Li, Konstantinos Kallidromitis, Yusuke Kato, Kazuki Kozuka, Trevor Darrell Hierarchical Randomized Smoothing
Yan Scholten, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann High-Fidelity Audio Compression with Improved RVQGAN
Rithesh Kumar, Prem Seetharaman, Alejandro Luebs, Ishaan Kumar, Kundan Kumar Hokoff: Real Game Dataset from Honor of Kings and Its Offline Reinforcement Learning Benchmarks
Yun Qu, Boyuan Wang, Jianzhun Shao, Yuhang Jiang, Chen Chen, Zhenbin Ye, Liu Linc, Yang Feng, Lin Lai, Hongyang Qin, Minwen Deng, Juchao Zhuo, Deheng Ye, Qiang Fu, Yang Guang, Wei Yang, Lanxiao Huang, Xiangyang Ji Holistic Evaluation of Text-to-Image Models
Tony Lee, Michihiro Yasunaga, Chenlin Meng, Yifan Mai, Joon Sung Park, Agrim Gupta, Yunzhi Zhang, Deepak Narayanan, Hannah Teufel, Marco Bellagente, Minguk Kang, Taesung Park, Jure Leskovec, Jun-Yan Zhu, Fei-Fei Li, Jiajun Wu, Stefano Ermon, Percy Liang Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data
Cheng-Hao Tu, Hong-You Chen, Zheda Mai, Jike Zhong, Vardaan Pahuja, Tanya Berger-Wolf, Song Gao, Charles Stewart, Yu Su, Wei-Lun Chao Honesty Is the Best Policy: Defining and Mitigating AI Deception
Francis Ward, Francesca Toni, Francesco Belardinelli, Tom Everitt HotBEV: Hardware-Oriented Transformer-Based Multi-View 3D Detector for BEV Perception
Peiyan Dong, Zhenglun Kong, Xin Meng, Pinrui Yu, Yifan Gong, Geng Yuan, Hao Tang, Yanzhi Wang How Do Minimum-Norm Shallow Denoisers Look in Function Space?
Chen Zeno, Greg Ongie, Yaniv Blumenfeld, Nir Weinberger, Daniel Soudry How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources
Yizhong Wang, Hamish Ivison, Pradeep Dasigi, Jack Hessel, Tushar Khot, Khyathi Chandu, David Wadden, Kelsey MacMillan, Noah A. Smith, Iz Beltagy, Hannaneh Hajishirzi How Re-Sampling Helps for Long-Tail Learning?
Jiang-Xin Shi, Tong Wei, Yuke Xiang, Yu-Feng Li How to Data in Datathons
Carlos Mougan, Richard Plant, Clare Teng, Marya Bazzi, Alvaro Cabrejas Egea, Ryan Chan, David Salvador Jasin, Martin Stoffel, Kirstie Whitaker, Jules Manser How to Fine-Tune the Model: Unified Model Shift and Model Bias Policy Optimization
Hai Zhang, Hang Yu, Junqiao Zhao, Di Zhang, Xiao Zhang, Hongtu Zhou, Chang Huang, Chen Ye How to Scale Your EMA
Dan Busbridge, Jason Ramapuram, Pierre Ablin, Tatiana Likhomanenko, Eeshan Gunesh Dhekane, Xavier Suau Cuadros, Russell Webb How2comm: Communication-Efficient and Collaboration-Pragmatic Multi-Agent Perception
Dingkang Yang, Kun Yang, Yuzheng Wang, Jing Liu, Zhi Xu, Rongbin Yin, Peng Zhai, Lihua Zhang HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text
Han Liu, Zhi Xu, Xiaotong Zhang, Feng Zhang, Fenglong Ma, Hongyang Chen, Hong Yu, Xianchao Zhang HT-Step: Aligning Instructional Articles with How-to Videos
Triantafyllos Afouras, Effrosyni Mavroudi, Tushar Nagarajan, Huiyu Wang, Lorenzo Torresani HuggingGPT: Solving AI Tasks with ChatGPT and Its Friends in Hugging Face
Yongliang Shen, Kaitao Song, Xu Tan, Dongsheng Li, Weiming Lu, Yueting Zhuang Human-Guided Complexity-Controlled Abstractions
Andi Peng, Mycal Tucker, Eoin Kenny, Noga Zaslavsky, Pulkit Agrawal, Julie A Shah HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution
Eric Nguyen, Michael Poli, Marjan Faizi, Armin Thomas, Michael Wornow, Callum Birch-Sykes, Stefano Massaroli, Aman Patel, Clayton Rabideau, Yoshua Bengio, Stefano Ermon, Christopher Ré, Stephen Baccus HyP-NeRF: Learning Improved NeRF Priors Using a HyperNetwork
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Orr Zohar, Shih-Cheng Huang, Kuan-Chieh Wang, Serena Yeung Low Tensor Rank Learning of Neural Dynamics
Arthur Pellegrino, N Alex Cayco Gajic, Angus Chadwick Low-Shot Object Learning with Mutual Exclusivity Bias
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Yuanqi Du, Yingheng Wang, Yining Huang, Jianan Canal Li, Yanqiao Zhu, Tian Xie, Chenru Duan, John Gregoire, Carla P. Gomes Machine Learning Detects Terminal Singularities
Tom Coates, Alexander Kasprzyk, Sara Veneziale MADG: Margin-Based Adversarial Learning for Domain Generalization
Aveen Dayal, K B Vimal, Linga Reddy Cenkeramaddi, C Mohan, Abhinav Kumar, Vineeth N Balasubramanian MADLAD-400: A Multilingual and Document-Level Large Audited Dataset
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Mikaela Angelina Uy, Kiyohiro Nakayama, Guandao Yang, Rahul Thomas, Leonidas Guibas, Ke Li NeRF-IBVS: Visual Servo Based on NeRF for Visual Localization and Navigation
Yuanze Wang, Yichao Yan, Dianxi Shi, Wenhan Zhu, Jianqiang Xia, Tan Jeff, Songchang Jin, Ke Gao, Xiaobo Li, Xiaokang Yang NetHack Is Hard to Hack
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Mariia Seleznova, Dana Weitzner, Raja Giryes, Gitta Kutyniok, Hung-Hsu Chou Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb
Jacob Zavatone-Veth, Paul Masset, William Tong, Joseph D. Zak, Venkatesh Murthy, Cengiz Pehlevan Neural Fields with Hard Constraints of Arbitrary Differential Order
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Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn Neural Graph Generation from Graph Statistics
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Matthew Wallingford, Vivek Ramanujan, Alex Fang, Aditya Kusupati, Roozbeh Mottaghi, Aniruddha Kembhavi, Ludwig Schmidt, Ali Farhadi Neural Processes with Stability
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Anwar Said, Roza Bayrak, Tyler Derr, Mudassir Shabbir, Daniel Moyer, Catie Chang, Xenofon Koutsoukos Newton–Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems
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Jindong Jiang, Fei Deng, Gautam Singh, Sungjin Ahn Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving
Xiaoyu Tian, Tao Jiang, Longfei Yun, Yucheng Mao, Huitong Yang, Yue Wang, Yilun Wang, Hang Zhao OceanBench: The Sea Surface Height Edition
J. Emmanuel Johnson, Quentin Febvre, Anastasiia Gorbunova, Sam Metref, Maxime Ballarotta, Julien Le Sommer, Ronan Fablet OFCOURSE: A Multi-Agent Reinforcement Learning Environment for Order Fulfillment
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Vaishnavh Nagarajan, Aditya K Menon, Srinadh Bhojanapalli, Hossein Mobahi, Sanjiv Kumar On the Constrained Time-Series Generation Problem
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Liang Chen, Shuming Ma, Dongdong Zhang, Furu Wei, Baobao Chang On the Robustness of Mechanism Design Under Total Variation Distance
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Gongjie Zhang, Jiahao Lin, Shuang Wu, Yilin Song, Zhipeng Luo, Yang Xue, Shijian Lu, Zuoguan Wang Online Nonstochastic Model-Free Reinforcement Learning
Udaya Ghai, Arushi Gupta, Wenhan Xia, Karan Singh, Elad Hazan Online PCA in Converging Self-Consistent Field Equations
Xihan Li, Xiang Chen, Rasul Tutunov, Haitham Bou Ammar, Lei Wang, Jun Wang Online Pricing for Multi-User Multi-Item Markets
Yigit Efe Erginbas, Thomas Courtade, Kannan Ramchandran, Soham Phade Online Robust Non-Stationary Estimation
Abishek Sankararaman, Balakrishnan Narayanaswamy Open Visual Knowledge Extraction via Relation-Oriented Multimodality Model Prompting
Hejie Cui, Xinyu Fang, Zihan Zhang, Ran Xu, Xuan Kan, Xin Liu, Yue Yu, Manling Li, Yangqiu Song, Carl Yang OpenAGI: When LLM Meets Domain Experts
Yingqiang Ge, Wenyue Hua, Kai Mei, Jianchao Ji, Juntao Tan, Shuyuan Xu, Zelong Li, Yongfeng Zhang OpenAssistant Conversations - Democratizing Large Language Model Alignment
Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi Rui Tam, Keith Stevens, Abdullah Barhoum, Duc Nguyen, Oliver Stanley, Richárd Nagyfi, Shahul Es, Sameer Suri, David Glushkov, Arnav Dantuluri, Andrew Maguire, Christoph Schuhmann, Huu Nguyen, Alexander Mattick OpenDataVal: A Unified Benchmark for Data Valuation
Kevin Jiang, Weixin Liang, James Y Zou, Yongchan Kwon OpenGSL: A Comprehensive Benchmark for Graph Structure Learning
Zhiyao Zhou, Sheng Zhou, Bochao Mao, Xuanyi Zhou, Jiawei Chen, Qiaoyu Tan, Daochen Zha, Yan Feng, Chun Chen, Can Wang OpenIllumination: A Multi-Illumination Dataset for Inverse Rendering Evaluation on Real Objects
Isabella Liu, Linghao Chen, Ziyang Fu, Liwen Wu, Haian Jin, Zhong Li, Chin Ming Ryan Wong, Yi Xu, Ravi Ramamoorthi, Zexiang Xu, Hao Su Opening the Vocabulary of Egocentric Actions
Dibyadip Chatterjee, Fadime Sener, Shugao Ma, Angela Yao OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD Mapping
Huijie Wang, Tianyu Li, Yang Li, Li Chen, Chonghao Sima, Zhenbo Liu, Bangjun Wang, Peijin Jia, Yuting Wang, Shengyin Jiang, Feng Wen, Hang Xu, Ping Luo, Junchi Yan, Wei Zhang, Hongyang Li OpenMask3D: Open-Vocabulary 3D Instance Segmentation
Ayca Takmaz, Elisabetta Fedele, Robert Sumner, Marc Pollefeys, Federico Tombari, Francis Engelmann OpenProteinSet: Training Data for Structural Biology at Scale
Gustaf Ahdritz, Nazim Bouatta, Sachin Kadyan, Lukas Jarosch, Dan Berenberg, Ian Fisk, Andrew Watkins, Stephen Ra, Richard Bonneau, Mohammed AlQuraishi OpenShape: Scaling up 3D Shape Representation Towards Open-World Understanding
Minghua Liu, Ruoxi Shi, Kaiming Kuang, Yinhao Zhu, Xuanlin Li, Shizhong Han, Hong Cai, Fatih Porikli, Hao Su OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
Cheng Tan, Siyuan Li, Zhangyang Gao, Wenfei Guan, Zedong Wang, Zicheng Liu, Lirong Wu, Stan Z. Li Operator Learning with Neural Fields: Tackling PDEs on General Geometries
Louis Serrano, Lise Le Boudec, Armand Kassaï Koupaï, Thomas X Wang, Yuan Yin, Jean-Noël Vittaut, Patrick Gallinari Optimal Learners for Realizable Regression: PAC Learning and Online Learning
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas Optimal Transport for Treatment Effect Estimation
Hao Wang, Jiajun Fan, Zhichao Chen, Haoxuan Li, Weiming Liu, Tianqiao Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang Optimal Transport Model Distributional Robustness
Van-Anh Nguyen, Trung Le, Anh Bui, Thanh-Toan Do, Dinh Phung Optimal Unbiased Randomizers for Regression with Label Differential Privacy
Ashwinkumar Badanidiyuru Varadaraja, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V Varadarajan, Chiyuan Zhang Optimistic Active Exploration of Dynamical Systems
Bhavya Sukhija, Lenart Treven, Cansu Sancaktar, Sebastian Blaes, Stelian Coros, Andreas Krause Optimistic Meta-Gradients
Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue, Hado P van Hasselt, András György, Satinder P. Singh Optimistic Rates for Multi-Task Representation Learning
Austin Watkins, Enayat Ullah, Thanh Nguyen-Tang, Raman Arora Optimizing over Trained GNNs via Symmetry Breaking
Shiqiang Zhang, Juan Campos, Christian Feldmann, David Walz, Frederik Sandfort, Miriam Mathea, Calvin Tsay, Ruth Misener Order Matters in the Presence of Dataset Imbalance for Multilingual Learning
Dami Choi, Derrick Xin, Hamid Dadkhahi, Justin Gilmer, Ankush Garg, Orhan Firat, Chih-Kuan Yeh, Andrew M Dai, Behrooz Ghorbani Ordering-Based Conditions for Global Convergence of Policy Gradient Methods
Jincheng Mei, Bo Dai, Alekh Agarwal, Mohammad Ghavamzadeh, Csaba Szepesvari, Dale Schuurmans Out-of-Distribution Detection Learning with Unreliable Out-of-Distribution Sources
Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han Outlier-Robust Gromov-Wasserstein for Graph Data
Lemin Kong, Jiajin Li, Jianheng Tang, Anthony Man-Cho So Outlier-Robust Wasserstein DRO
Sloan Nietert, Ziv Goldfeld, Soroosh Shafiee OV-PARTS: Towards Open-Vocabulary Part Segmentation
Meng Wei, Xiaoyu Yue, Wenwei Zhang, Shu Kong, Xihui Liu, Jiangmiao Pang P-Flow: A Fast and Data-Efficient Zero-Shot TTS Through Speech Prompting
Sungwon Kim, Kevin Shih, Rohan Badlani, Joao Felipe Santos, Evelina Bakhturina, Mikyas Desta, Rafael Valle, Sungroh Yoon, Bryan Catanzaro PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction
Apoorva Sharma, Sushant Veer, Asher Hancock, Heng Yang, Marco Pavone, Anirudha Majumdar PAD: A Dataset and Benchmark for Pose-Agnostic Anomaly Detection
Qiang Zhou, Weize Li, Lihan Jiang, Guoliang Wang, Guyue Zhou, Shanghang Zhang, Hao Zhao PaintSeg: Painting Pixels for Training-Free Segmentation
Xiang Li, Chung-Ching Lin, Yinpeng Chen, Zicheng Liu, Jinglu Wang, Rita Singh, Bhiksha Raj Pairwise Causality Guided Transformers for Event Sequences
Xiao Shou, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Oktie Hassanzadeh, Kristin P Bennett PanoGRF: Generalizable Spherical Radiance Fields for Wide-Baseline Panoramas
Zheng Chen, Yan-Pei Cao, Yuan-Chen Guo, Chen Wang, Ying Shan, Song-Hai Zhang PAPR: Proximity Attention Point Rendering
Yanshu Zhang, Shichong Peng, Alireza Moazeni, Ke Li ParaFuzz: An Interpretability-Driven Technique for Detecting Poisoned Samples in NLP
Lu Yan, Zhuo Zhang, Guanhong Tao, Kaiyuan Zhang, Xuan Chen, Guangyu Shen, Xiangyu Zhang Parallel Sampling of Diffusion Models
Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, Nima Anari Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-Term Dependencies
Wei Fang, Zhaofei Yu, Zhaokun Zhou, Ding Chen, Yanqi Chen, Zhengyu Ma, Timothée Masquelier, Yonghong Tian Parallel Submodular Function Minimization
Deeparnab Chakrabarty, Andrei Graur, Haotian Jiang, Aaron Sidford Parallel-Mentoring for Offline Model-Based Optimization
Can Chen, Christopher Beckham, Zixuan Liu, Xue Liu, Chris Pal Parameter-Efficient Tuning of Large-Scale Multimodal Foundation Model
Haixin Wang, Xinlong Yang, Jianlong Chang, Dian Jin, Jinan Sun, Shikun Zhang, Xiao Luo, Qi Tian Partial Matrix Completion
Elad Hazan, Adam Tauman Kalai, Varun Kanade, Clara Mohri, Y. Jennifer Sun Participatory Personalization in Classification
Hailey Joren, Chirag Nagpal, Katherine A. Heller, Berk Ustun Parts of Speech–Grounded Subspaces in Vision-Language Models
James Oldfield, Christos Tzelepis, Yannis Panagakis, Mihalis Nicolaou, Ioannis Patras Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang "Atlas" Wang, Weizhu Chen, Mingyuan Zhou Patch N’ Pack: NaViT, a Vision Transformer for Any Aspect Ratio and Resolution
Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim M Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey Gritsenko, Mario Lucic, Neil Houlsby Paxion: Patching Action Knowledge in Video-Language Foundation Models
Zhenhailong Wang, Ansel Blume, Sha Li, Genglin Liu, Jaemin Cho, Zineng Tang, Mohit Bansal, Heng Ji Payoff-Based Learning with Matrix Multiplicative Weights in Quantum Games
Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos, Jose Blanchet PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers
Phillip Lippe, Bas Veeling, Paris Perdikaris, Richard Turner, Johannes Brandstetter PDF: Point Diffusion Implicit Function for Large-Scale Scene Neural Representation
Yuhan Ding, Fukun Yin, Jiayuan Fan, Hui Li, Xin Chen, Wen Liu, Chongshan Lu, Gang Yu, Tao Chen Pengi: An Audio Language Model for Audio Tasks
Soham Deshmukh, Benjamin Elizalde, Rita Singh, Huaming Wang Perception Test: A Diagnostic Benchmark for Multimodal Video Models
Viorica Patraucean, Lucas Smaira, Ankush Gupta, Adria Recasens, Larisa Markeeva, Dylan Banarse, Skanda Koppula, Joseph Heyward, Mateusz Malinowski, Yi Yang, Carl Doersch, Tatiana Matejovicova, Yury Sulsky, Antoine Miech, Alexandre Fréchette, Hanna Klimczak, Raphael Koster, Junlin Zhang, Stephanie Winkler, Yusuf Aytar, Simon Osindero, Dima Damen, Andrew Zisserman, Joao Carreira Performance-Optimized Deep Neural Networks Are Evolving into Worse Models of Inferotemporal Visual Cortex
Drew Linsley, Ivan F Rodriguez Rodriguez, Thomas Fel, Michael Arcaro, Saloni Sharma, Margaret Livingstone, Thomas Serre Permutation Equivariant Neural Functionals
Allan Zhou, Kaien Yang, Kaylee Burns, Adriano Cardace, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn Persuading Farsighted Receivers in MDPs: The Power of Honesty
Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Mirco Mutti PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems
Jihui Jin, Etienne Ollivier, Richard Touret, Matthew McKinley, Karim Sabra, Justin Romberg Pgx: Hardware-Accelerated Parallel Game Simulators for Reinforcement Learning
Sotetsu Koyamada, Shinri Okano, Soichiro Nishimori, Yu Murata, Keigo Habara, Haruka Kita, Shin Ishii PHOTOSWAP: Personalized Subject Swapping in Images
Jing Gu, Yilin Wang, Nanxuan Zhao, Tsu-Jui Fu, Wei Xiong, Qing Liu, Zhifei Zhang, He Zhang, Jianming Zhang, HyunJoon Jung, Xin Eric Wang Physics-Informed Bayesian Optimization of Variational Quantum Circuits
Kim Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn, Klaus-Robert Müller, Paolo Stornati, Pan Kessel, Shinichi Nakajima Physion++: Evaluating Physical Scene Understanding That Requires Online Inference of Different Physical Properties
Hsiao-Yu Tung, Mingyu Ding, Zhenfang Chen, Daniel Bear, Chuang Gan, Josh Tenenbaum, Dan Yamins, Judith Fan, Kevin Smith Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation
Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, Omer Levy PIXIU: A Comprehensive Benchmark, Instruction Dataset and Large Language Model for Finance
Qianqian Xie, Weiguang Han, Xiao Zhang, Yanzhao Lai, Min Peng, Alejandro Lopez-Lira, Jimin Huang PlanE: Representation Learning over Planar Graphs
Radoslav Dimitrov, Zeyang Zhao, Ralph Abboud, Ismail Ceylan PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model
Yizhe Zhang, Jiatao Gu, Zhuofeng Wu, Shuangfei Zhai, Joshua Susskind, Navdeep Jaitly PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning
Hojoon Lee, Hanseul Cho, Hyunseung Kim, Daehoon Gwak, Joonkee Kim, Jaegul Choo, Se-Young Yun, Chulhee Yun Plug-and-Play Stability for Intracortical Brain-Computer Interfaces: A One-Year Demonstration of Seamless Brain-to-Text Communication
Chaofei Fan, Nick Hahn, Foram Kamdar, Donald Avansino, Guy Wilson, Leigh Hochberg, Krishna V Shenoy, Jaimie Henderson, Francis Willett Policy Gradient for Rectangular Robust Markov Decision Processes
Navdeep Kumar, Esther Derman, Matthieu Geist, Kfir Y. Levy, Shie Mannor Policy Space Diversity for Non-Transitive Games
Jian Yao, Weiming Liu, Haobo Fu, Yaodong Yang, Stephen McAleer, Qiang Fu, Wei Yang POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images
Antonin Vobecky, Oriane Siméoni, David Hurych, Spyridon Gidaris, Andrei Bursuc, Patrick Pérez, Josef Sivic PopSign ASL V1.0: An Isolated American Sign Language Dataset Collected via Smartphones
Thad Starner, Sean Forbes, Matthew So, David R. Martin, Rohit Sridhar, Gururaj Deshpande, Sam Sepah, Sahir Shahryar, Khushi Bhardwaj, Tyler Kwok, Daksh Sehgal, Saad Hassan, Bill Neubauer, Sofia Vempala, Alec Tan, Jocelyn Heath, Unnathi Kumar, Priyanka Mosur, Tavenner Hall, Rajandeep Singh, Christopher Cui, Glenn Cameron, Sohier Dane, Garrett Tanzer Post Hoc Explanations of Language Models Can Improve Language Models
Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, Himabindu Lakkaraju Post-Processing Private Synthetic Data for Improving Utility on Selected Measures
Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Luhuan Wu, Brian Trippe, Christian Naesseth, David M. Blei, John P. Cunningham Practical Contextual Bandits with Feedback Graphs
Mengxiao Zhang, Yuheng Zhang, Olga Vrousgou, Haipeng Luo, Paul Mineiro Practical Equivariances via Relational Conditional Neural Processes
Daolang Huang, Manuel Haussmann, Ulpu Remes, St John, Grégoire Clarté, Kevin Luck, Samuel Kaski, Luigi Acerbi Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting
Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang Predicting a Protein's Stability Under a Million Mutations
Jeffrey Ouyang-Zhang, Daniel Diaz, Adam Klivans, Philipp Kraehenbuehl PreDiff: Precipitation Nowcasting with Latent Diffusion Models
Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle Maddix, Yi Zhu, Mu Li, Yuyang Wang Preference-Grounded Token-Level Guidance for Language Model Fine-Tuning
Shentao Yang, Shujian Zhang, Congying Xia, Yihao Feng, Caiming Xiong, Mingyuan Zhou PrimDiffusion: Volumetric Primitives Diffusion for 3D Human Generation
Zhaoxi Chen, Fangzhou Hong, Haiyi Mei, Guangcong Wang, Lei Yang, Ziwei Liu Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision
Zhiqing Sun, Yikang Shen, Qinhong Zhou, Hongxin Zhang, Zhenfang Chen, David Cox, Yiming Yang, Chuang Gan PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning
Neeratyoy Mallik, Edward Bergman, Carl Hvarfner, Danny Stoll, Maciej Janowski, Marius Lindauer, Luigi Nardi, Frank Hutter Prioritizing Samples in Reinforcement Learning with Reducible Loss
Shivakanth Sujit, Somjit Nath, Pedro Braga, Samira Ebrahimi Kahou Privacy Auditing with One (1) Training Run
Thomas Steinke, Milad Nasr, Matthew Jagielski Private Estimation Algorithms for Stochastic Block Models and Mixture Models
Hongjie Chen, Vincent Cohen-Addad, Tommaso d’Orsi, Alessandro Epasto, Jacob Imola, David Steurer, Stefan Tiegel Private Everlasting Prediction
Moni Naor, Kobbi Nissim, Uri Stemmer, Chao Yan Probabilistic Exponential Integrators
Nathanael Bosch, Philipp Hennig, Filip Tronarp PrObeD: Proactive Object Detection Wrapper
Vishal Asnani, Abhinav Kumar, Suya You, Xiaoming Liu ProBio: A Protocol-Guided Multimodal Dataset for Molecular Biology Lab
Jieming Cui, Ziren Gong, Baoxiong Jia, Siyuan Huang, Zilong Zheng, Jianzhu Ma, Yixin Zhu PRODIGY: Enabling In-Context Learning over Graphs
Qian Huang, Hongyu Ren, Peng Chen, Gregor Kržmanc, Daniel Zeng, Percy Liang, Jure Leskovec Progressive Ensemble Distillation: Building Ensembles for Efficient Inference
Don Dennis, Abhishek Shetty, Anish Prasad Sevekari, Kazuhito Koishida, Virginia Smith Promises and Pitfalls of Threshold-Based Auto-Labeling
Harit Vishwakarma, Heguang Lin, Frederic Sala, Ramya Korlakai Vinayak Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition
Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alexander J Smola, Xu Sun Prompt-Augmented Temporal Point Process for Streaming Event Sequence
Siqiao Xue, Yan Wang, Zhixuan Chu, Xiaoming Shi, Caigao Jiang, Hongyan Hao, Gangwei Jiang, Xiaoyun Feng, James Zhang, Jun Zhou PromptIR: Prompting for All-in-One Image Restoration
Vaishnav Potlapalli, Syed Waqas Zamir, Salman H Khan, Fahad Shahbaz Khan PromptRestorer: A Prompting Image Restoration Method with Degradation Perception
Cong Wang, Jinshan Pan, Wei Wang, Jiangxin Dong, Mengzhu Wang, Yakun Ju, Junyang Chen Propagating Knowledge Updates to LMs Through Distillation
Shankar Padmanabhan, Yasumasa Onoe, Michael Zhang, Greg Durrett, Eunsol Choi ProPILE: Probing Privacy Leakage in Large Language Models
Siwon Kim, Sangdoo Yun, Hwaran Lee, Martin Gubri, Sungroh Yoon, Seong Joon Oh Protein Design with Guided Discrete Diffusion
Nate Gruver, Samuel Stanton, Nathan Frey, Tim G. J. Rudner, Isidro Hotzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew G Wilson ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design
Pascal Notin, Aaron Kollasch, Daniel Ritter, Lood van Niekerk, Steffanie Paul, Han Spinner, Nathan Rollins, Ada Shaw, Rose Orenbuch, Ruben Weitzman, Jonathan Frazer, Mafalda Dias, Dinko Franceschi, Yarin Gal, Debora Marks PROTES: Probabilistic Optimization with Tensor Sampling
Anastasiia Batsheva, Andrei Chertkov, Gleb Ryzhakov, Ivan Oseledets Prototypical Variational Autoencoder for 3D Few-Shot Object Detection
Weiliang Tang, Biqi Yang, Xianzhi Li, Yun-Hui Liu, Pheng-Ann Heng, Chi-Wing Fu Provable Benefits of Score Matching
Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski Provable Training for Graph Contrastive Learning
Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi Provably Bounding Neural Network Preimages
Suhas Kotha, Christopher Brix, J. Zico Kolter, Krishnamurthy Dvijotham, Huan Zhang Proximity-Informed Calibration for Deep Neural Networks
Miao Xiong, Ailin Deng, Pang Wei W Koh, Jiaying Wu, Shen Li, Jianqing Xu, Bryan Hooi Pruning vs Quantization: Which Is Better?
Andrey Kuzmin, Markus Nagel, Mart van Baalen, Arash Behboodi, Tijmen Blankevoort Pseudo-Likelihood Inference
Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan R Peters PTQD: Accurate Post-Training Quantization for Diffusion Models
Yefei He, Luping Liu, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari Morcos Punctuation-Level Attack: Single-Shot and Single Punctuation Can Fool Text Models
Wenqiang Wang, Chongyang Du, Tao Wang, Kaihao Zhang, Wenhan Luo, Lin Ma, Wei Liu, Xiaochun Cao Puzzlefusion: Unleashing the Power of Diffusion Models for Spatial Puzzle Solving
Sepidehsadat Hossieni, Mohammad Amin Shabani, Saghar Irandoust, Yasutaka Furukawa PyNeRF: Pyramidal Neural Radiance Fields
Haithem Turki, Michael Zollhöfer, Christian Richardt, Deva Ramanan Q-DM: An Efficient Low-Bit Quantized Diffusion Model
Yanjing Li, Sheng Xu, Xianbin Cao, Xiao Sun, Baochang Zhang QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules
Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji QLoRA: Efficient Finetuning of Quantized LLMs
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke Zettlemoyer Quantification of Uncertainty with Adversarial Models
Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Günter Klambauer, Sepp Hochreiter Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework
Paul Pu Liang, Yun Cheng, Xiang Fan, Chun Kai Ling, Suzanne Nie, Richard Chen, Zihao Deng, Nicholas Allen, Randy Auerbach, Faisal Mahmood, Ruslan Salakhutdinov, Louis-Philippe Morency QuantSR: Accurate Low-Bit Quantization for Efficient Image Super-Resolution
Haotong Qin, Yulun Zhang, Yifu Ding, Yifan Liu, Xianglong Liu, Martin Danelljan, Fisher Yu Quantum Bayesian Optimization
Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet Quasi-Monte Carlo Graph Random Features
Isaac Reid, Krzysztof M Choromanski, Adrian Weller Query-Based Temporal Fusion with Explicit Motion for 3D Object Detection
Jinghua Hou, Zhe Liu, Dingkang Liang, Zhikang Zou, Xiaoqing Ye, Xiang Bai Quilt-1m: One Million Image-Text Pairs for Histopathology
Wisdom Ikezogwo, Saygin Seyfioglu, Fatemeh Ghezloo, Dylan Geva, Fatwir Sheikh Mohammed, Pavan Kumar Anand, Ranjay Krishna, Linda G. Shapiro RaLEs: A Benchmark for Radiology Language Evaluations
Juanma Zambrano Chaves, Nandita Bhaskhar, Maayane Attias, Jean-Benoit Delbrouck, Daniel Rubin, Andreas Loening, Curtis Langlotz, Akshay Chaudhari Rank-DETR for High Quality Object Detection
Yifan Pu, Weicong Liang, Yiduo Hao, Yuhui Yuan, Yukang Yang, Chao Zhang, Han Hu, Gao Huang RanPAC: Random Projections and Pre-Trained Models for Continual Learning
Mark D. McDonnell, Dong Gong, Amin Parvaneh, Ehsan Abbasnejad, Anton van den Hengel RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Paths
Zeyue Xue, Guanglu Song, Qiushan Guo, Boxiao Liu, Zhuofan Zong, Yu Liu, Ping Luo RD-Suite: A Benchmark for Ranking Distillation
Zhen Qin, Rolf Jagerman, Rama Kumar Pasumarthi, Honglei Zhuang, He Zhang, Aijun Bai, Kai Hui, Le Yan, Xuanhui Wang Reading Relevant Feature from Global Representation Memory for Visual Object Tracking
Xinyu Zhou, Pinxue Guo, Lingyi Hong, Jinglun Li, Wei Zhang, Weifeng Ge, Wenqiang Zhang Real-World Image Super-Resolution as Multi-Task Learning
Wenlong Zhang, Xiaohui Li, Guangyuan Shi, Xiangyu Chen, Yu Qiao, Xiaoyun Zhang, Xiao-Ming Wu, Chao Dong Real3D-AD: A Dataset of Point Cloud Anomaly Detection
Jiaqi Liu, Guoyang Xie, Ruitao Chen, Xinpeng Li, Jinbao Wang, Yong Liu, Chengjie Wang, Feng Zheng Realistic Synthetic Financial Transactions for Anti-Money Laundering Models
Erik Altman, Jovan Blanuša, Luc von Niederhäusern, Beni Egressy, Andreea Anghel, Kubilay Atasu RealTime QA: What's the Answer Right Now?
Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi, Ronan Le Bras, Akari Asai, Xinyan Yu, Dragomir Radev, Noah A. Smith, Yejin Choi, Kentaro Inui REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths
Xu Chen, Jingsen Zhang, Lei Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Rui Zhang, Li Chen, Xin Zhao, Ji-Rong Wen RECKONING: Reasoning Through Dynamic Knowledge Encoding
Zeming Chen, Gail Weiss, Eric Mitchell, Asli Celikyilmaz, Antoine Bosselut Recommender Systems with Generative Retrieval
Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Tran, Jonah Samost, Maciej Kula, Ed Chi, Maheswaran Sathiamoorthy Reconciling Competing Sampling Strategies of Network Embedding
Yuchen Yan, Baoyu Jing, Lihui Liu, Ruijie Wang, Jinning Li, Tarek Abdelzaher, Hanghang Tong Reconstructing the Mind's Eye: fMRI-to-Image with Contrastive Learning and Diffusion Priors
Paul Scotti, Atmadeep Banerjee, Jimmie Goode, Stepan Shabalin, Alex Nguyen, Ethan Cohen, Aidan Dempster, Nathalie Verlinde, Elad Yundler, David Weisberg, Kenneth A. Norman, Tanishq Abraham Recurrent Temporal Revision Graph Networks
Yizhou Chen, Anxiang Zeng, Qingtao Yu, Kerui Zhang, Cao Yuanpeng, Kangle Wu, Guangda Huzhang, Han Yu, Zhiming Zhou Red Teaming Deep Neural Networks with Feature Synthesis Tools
Stephen Casper, Tong Bu, Yuxiao Li, Jiawei Li, Kevin Zhang, Kaivalya Hariharan, Dylan Hadfield-Menell ReDS: Offline RL with Heteroskedastic Datasets via Support Constraints
Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine Reference-Based POMDPs
Edward Kim, Yohan Karunanayake, Hanna Kurniawati Refined Mechanism Design for Approximately Structured Priors via Active Regression
Christos Boutsikas, Petros Drineas, Marios Mertzanidis, Alexandros Psomas, Paritosh Verma Reflexion: Language Agents with Verbal Reinforcement Learning
Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, Shunyu Yao Regression with Cost-Based Rejection
Xin Cheng, Yuzhou Cao, Haobo Wang, Hongxin Wei, Bo An, Lei Feng Regret Matching+: (In)Stability and Fast Convergence in Games
Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo Regret Minimization via Saddle Point Optimization
Johannes Kirschner, Alireza Bakhtiari, Kushagra Chandak, Volodymyr Tkachuk, Csaba Szepesvari Regularity as Intrinsic Reward for Free Play
Cansu Sancaktar, Justus Piater, Georg Martius Regularizing Neural Networks with Meta-Learning Generative Models
Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima Reinforcement Learning with Fast and Forgetful Memory
Steven Morad, Ryan Kortvelesy, Stephan Liwicki, Amanda Prorok Reinforcement Learning with Simple Sequence Priors
Tankred Saanum, Noémi Éltető, Peter Dayan, Marcel Binz, Eric Schulz Reliable Learning in Challenging Environments
Maria-Florina F Balcan, Steve Hanneke, Rattana Pukdee, Dravyansh Sharma Reliable Off-Policy Learning for Dosage Combinations
Jonas Schweisthal, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation
Shuyang Sun, Weijun Wang, Andrew Howard, Qihang Yu, Philip Torr, Liang-Chieh Chen Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach
Haoxuan Li, Kunhan Wu, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Zhi Geng, Fuli Feng, Xiangnan He, Peng Wu RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-Fidelity Head Avatars
Dongwei Pan, Long Zhuo, Jingtan Piao, Huiwen Luo, Wei Cheng, Yuxin Wang, Siming Fan, Shengqi Liu, Lei Yang, Bo Dai, Ziwei Liu, Chen Change Loy, Chen Qian, Wayne Wu, Dahua Lin, Kwan-Yee Lin Renku: A Platform for Sustainable Data Science
Rok Roškar, Chandrasekhar Ramakrishnan, Michele Volpi, Fernando Perez-Cruz, Lilian Gasser, Firat Ozdemir, Patrick Paitz, Mohammad Alisafaee, Philipp Fischer, Ralf Grubenmann, Eliza Harris, Tasko Olevski, Carl Remlinger, Luis Salamanca, Elisabet Capon Garcia, Lorenzo Cavazzi, Jakub Chrobasik, Darlin Cordoba Osnas, Alessandro Degano, Jimena Dupre, Wesley Johnson, Eike Kettner, Laura Kinkead, Sean D. Murphy, Flora Thiebaut, Olivier Verscheure Replicability in Reinforcement Learning
Amin Karbasi, Grigoris Velegkas, Lin Yang, Felix Zhou Replicable Clustering
Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou Replicable Reinforcement Learning
Eric Eaton, Marcel Hussing, Michael J. Kearns, Jessica Sorrell Representation Equivalent Neural Operators: A Framework for Alias-Free Operator Learning
Francesca Bartolucci, Emmanuel de Bézenac, Bogdan Raonic, Roberto Molinaro, Siddhartha Mishra, Rima Alaifari Res-Tuning: A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone
Zeyinzi Jiang, Chaojie Mao, Ziyuan Huang, Ao Ma, Yiliang Lv, Yujun Shen, Deli Zhao, Jingren Zhou Residual Q-Learning: Offline and Online Policy Customization Without Value
Chenran Li, Chen Tang, Haruki Nishimura, Jean Mercat, Masayoshi Tomizuka, Wei Zhan Resilient Constrained Learning
Ignacio Hounie, Alejandro Ribeiro, Luiz F. O. Chamon ResMem: Learn What You Can and Memorize the REST
Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan, Zonglin Li, Ankit Rawat, Manzil Zaheer, Aditya K Menon, Sanjiv Kumar ResoNet: Noise-Trained Physics-Informed MRI Off-Resonance Correction
Alfredo De Goyeneche Macaya, Shreya Ramachandran, Ke Wang, Ekin Karasan, Joseph Y. Cheng, Stella X. Yu, Michael Lustig Responsible AI (RAI) Games and Ensembles
Yash Gupta, Runtian Zhai, Arun Suggala, Pradeep K. Ravikumar Restart Sampling for Improving Generative Processes
Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi Jaakkola Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition
Samuel Dooley, Rhea Sukthanker, John Dickerson, Colin White, Frank Hutter, Micah Goldblum Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?
Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hongning Wang, Haifeng Xu Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective
Chenyu You, Weicheng Dai, Yifei Min, Fenglin Liu, David Clifton, S. Kevin Zhou, Lawrence Staib, James Duncan Rethinking the Role of Token Retrieval in Multi-Vector Retrieval
Jinhyuk Lee, Zhuyun Dai, Sai Meher Karthik Duddu, Tao Lei, Iftekhar Naim, Ming-Wei Chang, Vincent Zhao Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules
Zhiyuan Liu, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua Retrieval-Augmented Multiple Instance Learning
Yufei Cui, Ziquan Liu, Yixin Chen, Yuchen Lu, Xinyue Yu, Xue Liu, Tei-Wei Kuo, Miguel Rodrigues, Chun Jason Xue, Antoni B. Chan RETVec: Resilient and Efficient Text Vectorizer
Elie Bursztein, Marina Zhang, Owen Vallis, Xinyu Jia, Alexey Kurakin Reusable Slotwise Mechanisms
Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Duy Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio Reusing Pretrained Models by Multi-Linear Operators for Efficient Training
Yu Pan, Ye Yuan, Yichun Yin, Zenglin Xu, Lifeng Shang, Xin Jiang, Qun Liu Reverse Engineering Self-Supervised Learning
Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-Grained Intersection over Union
Zifu Wang, Maxim Berman, Amal Rannen-Triki, Philip Torr, Devis Tuia, Tinne Tuytelaars, Luc V Gool, Jiaqian Yu, Matthew Blaschko Revisiting Out-of-Distribution Robustness in NLP: Benchmarks, Analysis, and LLMs Evaluations
Lifan Yuan, Yangyi Chen, Ganqu Cui, Hongcheng Gao, FangYuan Zou, Xingyi Cheng, Heng Ji, Zhiyuan Liu, Maosong Sun Revisiting the Evaluation of Image Synthesis with GANs
Mengping Yang, Ceyuan Yang, Yichi Zhang, Qingyan Bai, Yujun Shen, Bo Dai Revisiting the Minimalist Approach to Offline Reinforcement Learning
Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery
Katie Luo, Zhenzhen Liu, Xiangyu Chen, Yurong You, Sagie Benaim, Cheng Perng Phoo, Mark Campbell, Wen Sun, Bharath Hariharan, Kilian Q. Weinberger Reward Imputation with Sketching for Contextual Batched Bandits
Xiao Zhang, Ninglu Shao, Zihua Si, Jun Xu, Wenhan Wang, Hanjing Su, Ji-Rong Wen Rewarded Soups: Towards Pareto-Optimal Alignment by Interpolating Weights Fine-Tuned on Diverse Rewards
Alexandre Rame, Guillaume Couairon, Corentin Dancette, Jean-Baptiste Gaya, Mustafa Shukor, Laure Soulier, Matthieu Cord REx: Data-Free Residual Quantization Error Expansion
Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly RGMIL: Guide Your Multiple-Instance Learning Model with Regressor
Zhaolong Du, Shasha Mao, Yimeng Zhang, Shuiping Gou, Licheng Jiao, Lin Xiong Riemannian Laplace Approximations for Bayesian Neural Networks
Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis Riemannian Projection-Free Online Learning
Zihao Hu, Guanghui Wang, Jacob D. Abernethy Riemannian Residual Neural Networks
Isay Katsman, Eric Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser Nam Lim, Christopher M De Sa Riemannian Stochastic Optimization Methods Avoid Strict Saddle Points
Ya-Ping Hsieh, Mohammad Reza Karimi Jaghargh, Andreas Krause, Panayotis Mertikopoulos RIO: A Benchmark for Reasoning Intention-Oriented Objects in Open Environments
Mengxue Qu, Yu Wu, Wu Liu, Xiaodan Liang, Jingkuan Song, Yao Zhao, Yunchao Wei RiskQ: Risk-Sensitive Multi-Agent Reinforcement Learning Value Factorization
Siqi Shen, Chennan Ma, Chao Li, Weiquan Liu, Yongquan Fu, Songzhu Mei, Xinwang Liu, Cheng Wang RoboCLIP: One Demonstration Is Enough to Learn Robot Policies
Sumedh Sontakke, Jesse Zhang, Séb Arnold, Karl Pertsch, Erdem Bıyık, Dorsa Sadigh, Chelsea Finn, Laurent Itti RoboDepth: Robust Out-of-Distribution Depth Estimation Under Corruptions
Lingdong Kong, Shaoyuan Xie, Hanjiang Hu, Lai Xing Ng, Benoit Cottereau, Wei Tsang Ooi RoboHive: A Unified Framework for Robot Learning
Vikash Kumar, Rutav Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Abhishek Gupta, Aravind Rajeswaran Robust and Actively Secure Serverless Collaborative Learning
Nicholas Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang Robust Bayesian Satisficing
Artun Saday, Y. Cahit Yıldırım, Cem Tekin Robust Concept Erasure via Kernelized Rate-Distortion Maximization
Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi Robust Low-Rank Training via Approximate Orthonormal Constraints
Dayana Savostianova, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco Rotating Features for Object Discovery
Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling rPPG-Toolbox: Deep Remote PPG Toolbox
Xin Liu, Girish Narayanswamy, Akshay Paruchuri, Xiaoyu Zhang, Jiankai Tang, Yuzhe Zhang, Roni Sengupta, Shwetak Patel, Yuntao Wang, Daniel McDuff RRHF: Rank Responses to Align Language Models with Human Feedback
Hongyi Yuan, Zheng Yuan, Chuanqi Tan, Wei Wang, Songfang Huang, Fei Huang RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion
Zhuoqun Huang, Neil G Marchant, Keane Lucas, Lujo Bauer, Olga Ohrimenko, Benjamin I. Rubinstein RVD: A Handheld Device-Based Fundus Video Dataset for Retinal Vessel Segmentation
Md Wahiduzzaman Khan, Hongwei Sheng, Hu Zhang, Heming Du, Sen Wang, Minas Coroneo, Farshid Hajati, Sahar Shariflou, Michael Kalloniatis, Jack Phu, Ashish Agar, Zi Huang, S.Mojtaba Golzan, Xin Yu SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models
Shuchen Xue, Mingyang Yi, Weijian Luo, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations
Youngsoo Jang, Geon-Hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim, Honglak Lee, Moontae Lee Safety Gymnasium: A Unified Safe Reinforcement Learning Benchmark
Jiaming Ji, Borong Zhang, Jiayi Zhou, Xuehai Pan, Weidong Huang, Ruiyang Sun, Yiran Geng, Yifan Zhong, Josef Dai, Yaodong Yang SALSA VERDE: A Machine Learning Attack on LWE with Sparse Small Secrets
Cathy Li, Emily Wenger, Zeyuan Allen-Zhu, Francois Charton, Kristin E. Lauter Sample-Efficient Multi-Objective Molecular Optimization with GFlowNets
Yiheng Zhu, Jialu Wu, Chaowen Hu, Jiahuan Yan, Kim Hsieh, Tingjun Hou, Jian Wu Sampling from Gaussian Process Posteriors Using Stochastic Gradient Descent
Jihao Andreas Lin, Javier Antorán, Shreyas Padhy, David Janz, José Miguel Hernández-Lobato, Alexander Terenin Sampling Weights of Deep Neural Networks
Erik L Bolager, Iryna Burak, Chinmay Datar, Qing Sun, Felix Dietrich SARAMIS: Simulation Assets for Robotic Assisted and Minimally Invasive Surgery
Nina Montana-Brown, Shaheer U. Saeed, Ahmed Abdulaal, Thomas Dowrick, Yakup Kilic, Sophie Wilkinson, Jack Gao, Meghavi Mashar, Chloe He, Alkisti Stavropoulou, Emma Thomson, Zachary MC Baum, Simone Foti, Brian Davidson, Yipeng Hu, Matthew Clarkson SatBird: A Dataset for Bird Species Distribution Modeling Using Remote Sensing and Citizen Science Data
Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi, Hugo Larochelle, David Rolnick Scalable 3D Captioning with Pretrained Models
Tiange Luo, Chris Rockwell, Honglak Lee, Justin Johnson Scalable Fair Influence Maximization
Xiaobin Rui, Zhixiao Wang, Jiayu Zhao, Lichao Sun, Wei Chen Scalable Membership Inference Attacks via Quantile Regression
Martin Bertran, Shuai Tang, Aaron Roth, Michael J. Kearns, Jamie H Morgenstern, Steven Z. Wu Scaling Data-Constrained Language Models
Niklas Muennighoff, Alexander Rush, Boaz Barak, Teven Le Scao, Nouamane Tazi, Aleksandra Piktus, Sampo Pyysalo, Thomas Wolf, Colin A Raffel Scaling Laws for Hyperparameter Optimization
Arlind Kadra, Maciej Janowski, Martin Wistuba, Josif Grabocka Scaling Laws for Language Encoding Models in fMRI
Richard Antonello, Aditya Vaidya, Alexander Huth Scaling MLPs: A Tale of Inductive Bias
Gregor Bachmann, Sotiris Anagnostidis, Thomas Hofmann Scaling Open-Vocabulary Object Detection
Matthias Minderer, Alexey Gritsenko, Neil Houlsby Scaling Riemannian Diffusion Models
Aaron Lou, Minkai Xu, Adam Farris, Stefano Ermon Scenario Diffusion: Controllable Driving Scenario Generation with Diffusion
Ethan Pronovost, Meghana Reddy Ganesina, Noureldin Hendy, Zeyu Wang, Andres Morales, Kai Wang, Nick Roy SceneScape: Text-Driven Consistent Scene Generation
Rafail Fridman, Amit Abecasis, Yoni Kasten, Tali Dekel Schema-Learning and Rebinding as Mechanisms of In-Context Learning and Emergence
Sivaramakrishnan Swaminathan, Antoine Dedieu, Rajkumar Vasudeva Raju, Murray Shanahan, Miguel Lazaro-Gredilla, Dileep George Scientific Document Retrieval Using Multi-Level Aspect-Based Queries
Jianyou Wang, Kaicheng Wang, Xiaoyue Wang, Prudhviraj Naidu, Leon Bergen, Ramamohan Paturi Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time
Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, Anshumali Shrivastava Score-Based Data Assimilation
François Rozet, Gilles Louppe Score-Based Generative Modeling Through Stochastic Evolution Equations in Hilbert Spaces
Sungbin Lim, Eun Bi Yoon, Taehyun Byun, Taewon Kang, Seungwoo Kim, Kyungjae Lee, Sungjoon Choi Score-Based Generative Models with Lévy Processes
Eun Bi Yoon, Keehun Park, Sungwoong Kim, Sungbin Lim Score-Based Source Separation with Applications to Digital Communication Signals
Tejas Jayashankar, Gary C.F. Lee, Alejandro Lancho, Amir Weiss, Yury Polyanskiy, Gregory Wornell SE(3) Equivariant Augmented Coupling Flows
Laurence Midgley, Vincent Stimper, Javier Antorán, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato Secure Out-of-Distribution Task Generalization with Energy-Based Models
Shengzhuang Chen, Long-Kai Huang, Jonathan Richard Schwarz, Yilun Du, Ying Wei SEEDS: Exponential SDE Solvers for Fast High-Quality Sampling from Diffusion Models
Martin Gonzalez, Nelson Fernandez Pinto, Thuy Tran, Elies Gherbi, Hatem Hajri, Nader Masmoudi SEENN: Towards Temporal Spiking Early Exit Neural Networks
Yuhang Li, Tamar Geller, Youngeun Kim, Priyadarshini Panda SEGA: Instructing Text-to-Image Models Using Semantic Guidance
Manuel Brack, Felix Friedrich, Dominik Hintersdorf, Lukas Struppek, Patrick Schramowski, Kristian Kersting Segment Any Point Cloud Sequences by Distilling Vision Foundation Models
Youquan Liu, Lingdong Kong, Jun Cen, Runnan Chen, Wenwei Zhang, Liang Pan, Kai Chen, Ziwei Liu Segment Anything in 3D with NeRFs
Jiazhong Cen, Zanwei Zhou, Jiemin Fang, Chen Yang, Wei Shen, Lingxi Xie, Dongsheng Jiang, Xiaopeng Zhang, Qi Tian Segment Anything in High Quality
Lei Ke, Mingqiao Ye, Martin Danelljan, Yifan Liu, Yu-Wing Tai, Chi-Keung Tang, Fisher Yu Segment Everything Everywhere All at Once
Xueyan Zou, Jianwei Yang, Hao Zhang, Feng Li, Linjie Li, Jianfeng Wang, Lijuan Wang, Jianfeng Gao, Yong Jae Lee Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning
Yihua Zhang, Yimeng Zhang, Aochuan Chen, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Mingyi Hong, Shiyu Chang, Sijia Liu Self-Evaluation Guided Beam Search for Reasoning
Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, James Xu Zhao, Min-Yen Kan, Junxian He, Michael Xie Self-Predictive Universal AI
Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Grégoire Delétang, Kevin Li, Joel Veness Self-Refine: Iterative Refinement with Self-Feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark Self-Supervised Graph Neural Networks via Low-Rank Decomposition
Liang Yang, Runjie Shi, Qiuliang Zhang, Bingxin Niu, Zhen Wang, Xiaochun Cao, Chuan Wang Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells
Rylan Schaeffer, Mikail Khona, Tzuhsuan Ma, Cristobal Eyzaguirre, Sanmi Koyejo, Ila Fiete Self-Supervised Learning with Lie Symmetries for Partial Differential Equations
Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Kiani Self-Supervised Visual Acoustic Matching
Arjun Somayazulu, Changan Chen, Kristen Grauman Semantic HELM: A Human-Readable Memory for Reinforcement Learning
Fabian Paischer, Thomas Adler, Markus Hofmarcher, Sepp Hochreiter Semantic Image Synthesis with Unconditional Generator
JungWoo Chae, Hyunin Cho, Sooyeon Go, Kyungmook Choi, Youngjung Uh Semi-Implicit Denoising Diffusion Models (SIDDMs)
Yanwu Xu, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, Kayhan Batmanghelich, Tingbo Hou Separable Physics-Informed Neural Networks
Junwoo Cho, Seungtae Nam, Hyunmo Yang, Seok-Bae Yun, Youngjoon Hong, Eunbyung Park SEVA: Leveraging Sketches to Evaluate Alignment Between Human and Machine Visual Abstraction
Kushin Mukherjee, Holly Huey, Xuanchen Lu, Yael Vinker, Rio Aguina-Kang, Ariel Shamir, Judith Fan SG×P : A Sorghum Genotype × Phenotype Prediction Dataset and Benchmark
Zeyu Zhang, Robert Pless, Nadia Shakoor, Austin Carnahan, Abby Stylianou SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations
Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan SHAP-IQ: Unified Approximation of Any-Order Shapley Interactions
Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer Sharp Calibrated Gaussian Processes
Alexandre Capone, Sandra Hirche, Geoff Pleiss Sharp Spectral Rates for Koopman Operator Learning
Vladimir Kostic, Karim Lounici, Pietro Novelli, Massimiliano Pontil Sharpness-Aware Minimization Leads to Low-Rank Features
Maksym Andriushchenko, Dara Bahri, Hossein Mobahi, Nicolas Flammarion Sheaf Hypergraph Networks
Iulia Duta, Giulia Cassarà, Fabrizio Silvestri, Pietro Lió Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
Hammaad Adam, Fan Yin, Huibin Hu, Neil Tenenholtz, Lorin Crawford, Lester W. Mackey, Allison Koenecke Should We Learn Most Likely Functions or Parameters?
Shikai Qiu, Tim G. J. Rudner, Sanyam Kapoor, Andrew G Wilson Siamese Masked Autoencoders
Agrim Gupta, Jiajun Wu, Jia Deng, Fei-Fei Li Similarity-Based Cooperative Equilibrium
Caspar Oesterheld, Johannes Treutlein, Roger B Grosse, Vincent Conitzer, Jakob Foerster SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling
Jiaxiang Dong, Haixu Wu, Haoran Zhang, Li Zhang, Jianmin Wang, Mingsheng Long Simple and Controllable Music Generation
Jade Copet, Felix Kreuk, Itai Gat, Tal Remez, David Kant, Gabriel Synnaeve, Yossi Adi, Alexandre Defossez Simple, Scalable and Effective Clustering via One-Dimensional Projections
Moses Charikar, Monika Henzinger, Lunjia Hu, Maximilian Vötsch, Erik Waingarten Simplicity Bias in 1-Hidden Layer Neural Networks
Depen Morwani, Jatin Batra, Prateek Jain, Praneeth Netrapalli Simplifying Neural Network Training Under Class Imbalance
Ravid Shwartz-Ziv, Micah Goldblum, Yucen Li, C. Bayan Bruss, Andrew G Wilson Single-Stage Visual Query Localization in Egocentric Videos
Hanwen Jiang, Santhosh Kumar Ramakrishnan, Kristen Grauman SiT Dataset: Socially Interactive Pedestrian Trajectory Dataset for Social Navigation Robots
Jong Wook Bae, Jungho Kim, Junyong Yun, Changwon Kang, Jeongseon Choi, Chanhyeok Kim, Junho Lee, Jungwook Choi, Jun Won Choi Skill-It! a Data-Driven Skills Framework for Understanding and Training Language Models
Mayee Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré SLAM: Student-Label Mixing for Distillation with Unlabeled Examples
Vasilis Kontonis, Fotis Iliopoulos, Khoa Trinh, Cenk Baykal, Gaurav Menghani, Erik Vee SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning
Benjamin Ellis, Jonathan Cook, Skander Moalla, Mikayel Samvelyan, Mingfei Sun, Anuj Mahajan, Jakob Foerster, Shimon Whiteson Small Batch Deep Reinforcement Learning
Johan Obando Ceron, Marc Bellemare, Pablo Samuel Castro SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation
Mengcheng Lan, Xinjiang Wang, Yiping Ke, Jiaxing Xu, Litong Feng, Wayne Zhang SmoothHess: ReLU Network Feature Interactions via Stein's Lemma
Max Torop, Aria Masoomi, Davin Hill, Kivanc Kose, Stratis Ioannidis, Jennifer Dy SMPLer-X: Scaling up Expressive Human Pose and Shape Estimation
Zhongang Cai, Wanqi Yin, Ailing Zeng, Chen Wei, Qingping Sun, Wang Yanjun, Hui En Pang, Haiyi Mei, Mingyuan Zhang, Lei Zhang, Chen Change Loy, Lei Yang, Ziwei Liu SnapFusion: Text-to-Image Diffusion Model on Mobile Devices Within Two Seconds
Yanyu Li, Huan Wang, Qing Jin, Ju Hu, Pavlo Chemerys, Yun Fu, Yanzhi Wang, Sergey Tulyakov, Jian Ren SOAR: Improved Indexing for Approximate Nearest Neighbor Search
Philip Sun, David Simcha, Dave Dopson, Ruiqi Guo, Sanjiv Kumar SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation
Zhuoyan Luo, Yicheng Xiao, Yong Liu, Shuyan Li, Yitong Wang, Yansong Tang, Xiu Li, Yujiu Yang Social Motion Prediction with Cognitive Hierarchies
Wentao Zhu, Jason Qin, Yuke Lou, Hang Ye, Xiaoxuan Ma, Hai Ci, Yizhou Wang SODA: Robust Training of Test-Time Data Adaptors
Zige Wang, Yonggang Zhang, Zhen Fang, Long Lan, Wenjing Yang, Bo Han Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models
Litu Rout, Negin Raoof, Giannis Daras, Constantine Caramanis, Alex Dimakis, Sanjay Shakkottai Sorting with Predictions
Xingjian Bai, Christian Coester SoTTA: Robust Test-Time Adaptation on Noisy Data Streams
Taesik Gong, Yewon Kim, Taeckyung Lee, Sorn Chottananurak, Sung-Ju Lee SoundCam: A Dataset for Finding Humans Using Room Acoustics
Mason Wang, Samuel Clarke, Jui-Hsien Wang, Ruohan Gao, Jiajun Wu Sounding Bodies: Modeling 3D Spatial Sound of Humans Using Body Pose and Audio
Xudong Xu, Dejan Markovic, Jacob Sandakly, Todd Keebler, Steven Krenn, Alexander Richard SPA: A Graph Spectral Alignment Perspective for Domain Adaptation
Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, Junbo Zhao SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs
Lijun Yu, Yong Cheng, Zhiruo Wang, Vivek Kumar, Wolfgang Macherey, Yanping Huang, David A. Ross, Irfan A. Essa, Yonatan Bisk, Ming-Hsuan Yang, Kevin P. Murphy, Alexander Hauptmann, Lu Jiang Sparse Modular Activation for Efficient Sequence Modeling
Liliang Ren, Yang Liu, Shuohang Wang, Yichong Xu, Chenguang Zhu, Cheng Xiang Zhai Sparsity-Preserving Differentially Private Training of Large Embedding Models
Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang SpecTr: Fast Speculative Decoding via Optimal Transport
Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix Yu Spectral Co-Distillation for Personalized Federated Learning
Zihan Chen, Howard Hua Yang, Tony Quek, Kai Fong Ernest Chong Spectral Evolution and Invariance in Linear-Width Neural Networks
Zhichao Wang, Andrew Engel, Anand D Sarwate, Ioana Dumitriu, Tony Chiang Spectral Invariant Learning for Dynamic Graphs Under Distribution Shifts
Zeyang Zhang, Xin Wang, Ziwei Zhang, Zhou Qin, Weigao Wen, Hui Xue', Haoyang Li, Wenwu Zhu Speculative Decoding with Big Little Decoder
Sehoon Kim, Karttikeya Mangalam, Suhong Moon, Jitendra Malik, Michael W. Mahoney, Amir Gholami, Kurt Keutzer Spike-Driven Transformer
Man Yao, JiaKui Hu, Zhaokun Zhou, Li Yuan, Yonghong Tian, Bo Xu, Guoqi Li Spiking PointNet: Spiking Neural Networks for Point Clouds
Dayong Ren, Zhe Ma, Yuanpei Chen, Weihang Peng, Xiaode Liu, Yuhan Zhang, Yufei Guo SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agents
Shuzheng Si, Wentao Ma, Haoyu Gao, Yuchuan Wu, Ting-En Lin, Yinpei Dai, Hangyu Li, Rui Yan, Fei Huang, Yongbin Li SPRING: Studying Papers and Reasoning to Play Games
Yue Wu, So Yeon Min, Shrimai Prabhumoye, Yonatan Bisk, Ruslan Salakhutdinov, Amos Azaria, Tom M. Mitchell, Yuanzhi Li Spuriosity Didn’t Kill the Classifier: Using Invariant Predictions to Harness Spurious Features
Cian Eastwood, Shashank Singh, Andrei L Nicolicioiu, Marin Vlastelica Pogančić, Julius von Kügelgen, Bernhard Schölkopf SSL4EO-L: Datasets and Foundation Models for Landsat Imagery
Adam Stewart, Nils Lehmann, Isaac Corley, Yi Wang, Yi-Chia Chang, Nassim Ait Ait Ali Braham, Shradha Sehgal, Caleb Robinson, Arindam Banerjee Stable and Low-Precision Training for Large-Scale Vision-Language Models
Mitchell Wortsman, Tim Dettmers, Luke Zettlemoyer, Ari Morcos, Ali Farhadi, Ludwig Schmidt Stable Bias: Evaluating Societal Representations in Diffusion Models
Sasha Luccioni, Christopher Akiki, Margaret Mitchell, Yacine Jernite Stable Diffusion Is Unstable
Chengbin Du, Yanxi Li, Zhongwei Qiu, Chang Xu StableFDG: Style and Attention Based Learning for Federated Domain Generalization
Jungwuk Park, Dong-Jun Han, Jinho Kim, Shiqiang Wang, Christopher Brinton, Jaekyun Moon Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmark
Zhengfei Kuang, Yunzhi Zhang, Hong-Xing Yu, Samir Agarwala, Elliott / Shangzhe Wu, Jiajun Wu Star-Shaped Denoising Diffusion Probabilistic Models
Andrey Okhotin, Dmitry Molchanov, Arkhipkin Vladimir, Grigory Bartosh, Viktor Ohanesian, Aibek Alanov, Dmitry P Vetrov STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events
Kazuki Shimada, Archontis Politis, Parthasaarathy Sudarsanam, Daniel A. Krause, Kengo Uchida, Sharath Adavanne, Aapo Hakala, Yuichiro Koyama, Naoya Takahashi, Shusuke Takahashi, Tuomas Virtanen, Yuki Mitsufuji State Regularized Policy Optimization on Data with Dynamics Shift
Zhenghai Xue, Qingpeng Cai, Shuchang Liu, Dong Zheng, Peng Jiang, Kun Gai, Bo An State Sequences Prediction via Fourier Transform for Representation Learning
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