Best Paper Awards

​

2026

• Model Change for Description Logic Concepts, Ana Ozaki, Jandson S. Ribeiro, Outstanding Paper
• Causal Structure Learning for Dynamical Systems with Theoretical Score Analysis, Nicholas Tagliapietra, Katharina Ensinger, Christoph Zimmer, Osman Mian, Outstanding Paper
• ReconVLA: Reconstructive Vision-Language-Action Model as Effective Robot Perceiver, Wenxuan Song, Ziyang Zhou, Han Zhao, Jiayi Chen, Pengxiang Ding, et al., Outstanding Paper
• LLM2CLIP: Powerful Language Model Unlocks Richer Cross-Modality Representation, Weiquan Huang, Aoqi Wu, Yifan Yang, Xufang Luo, Yuqing Yang, et al., Outstanding Paper
• High-pass Matters: Theoretical Insights and Sheaflet-Based Design for Hypergraph Neural Networks, Ming Li, Yujie Fang, Dongrui Shen, Han Feng, Xiaosheng Zhuang, et al., Outstanding Paper

• PlantTraitNet: An Uncertainty-Aware Multimodal Framework for Global-Scale Plant Trait Inference from Citizen Science Data, Ayushi Sharma, Johanna Trost, Daniel Lusk, Johannes Dollinger, et al., Outstanding Paper (AISI)
• Generalizable Slum Detection from Satellite Imagery with Mixture-of-Experts, Sumin Lee, Sungwon Park, Jeasurk Yang, Jihee Kim, Meeyoung Cha, Outstanding Paper (AISI)

​

2025

• Every Bit Helps: Achieving the Optimal Distortion with a Few Queries, Soroush Ebadian, Nisarg Shah, Outstanding Paper
• Efficient Rectification of Neuro-Symbolic Reasoning Inconsistencies by Abductive Reflection, Wen-Chao Hu, Wang-Zhou Dai, et al., Outstanding Paper
• Revelations: A Decidable Class of POMDPs with Omega-Regular Objectives, Marius Belly, Nathanael Fijalkow, et al., Outstanding Paper
• DivShift: Exploring Domain-Specific Distribution Shifts in Large-Scale Biodiversity Datasets, Elena Sierra, Lauren Gillespie, Moises Exposito Alonso, Outstanding Paper
• BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and RL, Artem Zholus, Maksim Kuznetsov, et al., Outstanding Paper

​

2024

• Reliable Conflictive Multi-view Learning, Cai Xu, Jiajun Si, et al., Outstanding Paper
• Proportional Aggregation of Preferences for Sequential Decision Making, Nikhil Chandak, Shashwat Goel, Dominik Peters, Outstanding Paper

​

2023

• Misspecification in Inverse Reinforcement Learning, Joar Skalse, Alessandro Abate, Outstanding Paper
• Decorate the Newcomers: Visual Domain Prompt for Continual Test Time Adaptation, Yulu Gan, Yan Bai, et al., Outstanding Student Paper

​

2022

• Certified Symmetry and Dominance Breaking for Combinatorial Optimisation, Bart Bogaerts, Stephan Gocht, et al., Distinguished Paper
• Sampling-Based Robust Control of Autonomous Systems with Non-Gaussian Noise, Thom S. Badings, Alessandro Abate, et al., Distinguished Paper

​

2021

• Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting, Haoyi Zhou, Shanghang Zhang, et al., Outstanding Paper
• Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory, Stefanos Leonardos, Georgios Piliouras, Outstanding Paper

​

2025

• Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention, Jingyang Yuan, Huazuo Gao, et al. (DeepSeek/PKU), Best Paper
• Fairness through Difference Awareness: Measuring Desired Group Discrimination in LLMs, Angelina Wang, Michelle Phan, et al., Best Paper
• Language Models Resist Alignment: Evidence From Data Compression, Jiaming Ji, Kaile Wang, et al., Best Paper
• AfriMed-QA: A Pan-African, Multi-Specialty, Medical QA Benchmark, Charles Nimo, Tobi Olatunji, et al., Best Paper

​

2024

• Mission: Impossible Language Models, Julie Kallini, Isabel Papadimitriou, et al., Best Paper
• Semisupervised Neural Proto-Language Reconstruction, Liang Lu, Peirong Xie, David R. Mortensen, Best Paper
• Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model, Ahmet Ustun, Viraat Aryabumi, et al., Best Paper
• Deciphering Oracle Bone Language with Diffusion Models, Haisu Guan, Huanxin Yang, et al., Best Paper

​

2023

• Do Androids Laugh at Electric Sheep? Humor “Understanding” Benchmarks from The New Yorker Caption Contest, Jack Hessel, Ana Marasovic, et al., Best Paper

​

2022

• Learned Incremental Representations for Parsing, Nikita Kitaev, Thomas Lu, Dan Klein, Best Paper

​

2021

• Vocabulary Learning via Optimal Transport for Neural Machine Translation, Jingjing Xu, Hao Zhou, et al., Best Paper

​

2025

• VGGT: Visual Geometry Grounded Transformer, Jianyuan Wang, Minghao Chen, et al., Best Paper
• Neural Inverse Rendering from Propagating Light, Anagh Malik, Benjamin Attal, et al., Best Student Paper
• Navigation World Models, Amir Bar, Gaoyue Zhou, et al., Honorable Mention
• MegaSaM: Accurate, Fast and Robust Structure and Motion from Casual Dynamic Videos, Zhengqi Li, Richard Tucker, et al., Honorable Mention

​

2024

• Generative Image Dynamics, Zhengqi Li, Richard Tucker, et al., Best Paper
• Rich Human Feedback for Text-to-Image Generation, Youwei Liang, Junfeng He, et al., Best Paper
• Mip-Splatting: Alias-free 3D Gaussian Splatting, Zehao Yu, Anpei Chen, et al., Best Student Paper
• BioCLIP: A Vision Foundation Model for the Tree of Life, Samuel Stevens, Jiaman Wu, et al., Best Student Paper

​

2023

• Planning-oriented Autonomous Driving (UniAD), Yihan Hu, Jiazhi Yang, et al., Best Paper
• Visual Programming: Compositional Visual Reasoning without Training, Tanmay Gupta, Aniruddha Kembhavi, Best Paper

​

2022

• Learning to Solve Hard Minimal Problems, Petr Hruby, Timothy Duff, et al., Best Paper
• EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points, Hansheng Chen, Pichao Wang, et al., Best Student Paper
• Dual-Shutter Optical Vibration Sensing, Mark Sheinin, Dorian Chan, et al., Honorable Mention

​

2021

• GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields, Michael Niemeyer, Andreas Geiger, Best Paper

​

2024

• Minimalist Vision with Freeform Pixels, Jeremy Klotz, Shree Nayar, Best Paper
• Rasterized Edge Gradients: Handling Discontinuities Differentially, Stanislav Pidhorskyi, Tomas Simon, et al., Honorable Mention
• Concept Arithmetics for Circumventing Concept Inhibition in Diffusion Models, Vitali Petsiuk, Kate Saenko, Honorable Mention

​

2022

• On the Versatile Uses of Partial Distance Correlation in Deep Learning, Xingjian Zhen, Zihang Meng, et al., Best Paper
• Pose-NDF: Modelling Human Pose Manifolds with Neural Distance Fields, Garvita Tiwari, Dimitrije Antic, et al., Honorable Mention

​

2025

• Infini-gram mini: Exact n-gram Search at the Internet Scale with FM-Index, Hao Xu, Jiacheng Liu, et al., Best Paper
• LingGym: How Far Are LLMs from Thinking Like Field Linguists?, Freda Shi, Changbing Yang, et al., Outstanding Paper

​

2024

• Pretraining Data Detection for Large Language Models: A Divergence-based Calibration Method, Weichao Zhang, et al., Best Paper
• An Image Speaks a Thousand Words, but Can Everyone Listen? On Image Transcreation for Cultural Relevance, Simran Khanuja, et al., Best Paper
• KidLM: Advancing Language Models for Children, Mir Tafseer Nayeem, Davood Rafiei, Best Resource Paper

​

2023

• Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs Through a Global Prompt Hacking Competition, Sander V. Schulhoff, et al., Best Paper

​

2022

• Abstract Visual Reasoning with Tangram Shapes, Anya Ji, Noriyuki Kojima, et al., Best Paper

​

2021

• Visually Grounded Reasoning across Languages and Cultures, Fangyu Liu, Emanuele Bugliarello, et al., Best Long Paper

​

2025

• BrickGPT: Generating Physically Stable and Buildable Brick Structures from Text, Ava Pun, Kangle Deng, et al., Best Paper (Marr Prize)

​

2023

• Adding Conditional Control to Text-to-Image Diffusion Models (ControlNet), Lvmin Zhang, Anyi Rao, Maneesh Agrawala, Best Paper (Marr Prize)
• Passive Ultra-Wideband Single-Photon Imaging, Mian Wei, Sotiris Nousias, et al., Best Paper (Marr Prize)
• Segment Anything, Alexander Kirillov, Eric Mintun, et al. (Meta), Honorable Mention
• Tracking Everything Everywhere All At Once, Qianqian Wang, Yen-Yu Chang, et al., Honorable Mention

​

2021

• Swin Transformer: Hierarchical Vision Transformer using Shifted Windows, Ze Liu, Yutong Lin, et al., Best Paper (Marr Prize)

​

2026

• Transformers are Inherently Succinct, Pascal Bergsträßer, Ryan Cotterell, Anthony Widjaja Lin, Outstanding Paper
• LLMs Get Lost In Multi-Turn Conversation, Philippe Laban, Hiroaki Hayashi, Yingbo Zhou, Jennifer Neville, Outstanding Paper
• The Polar Express: Optimal Matrix Sign Methods and their Application to the Muon Algorithm, Noah Amsel, David Persson, Christopher Musco, Robert M. Gower, Honorable Mention

​

2025

• Safety Alignment Should be Made More Than Just a Few Tokens Deep, Xiangyu Qi, Ashwinee Panda, et al., Outstanding Paper
• Learning Dynamics of LLM Finetuning, Yi Ren, Danica J. Sutherland, Outstanding Paper
• SAM 2: Segment Anything in Images and Videos, Nikhila Ravi, Valentin Gabeur, et al. (Meta), Outstanding Paper
• Data Shapley in One Training Run, Jiachen T. Wang, Prateek Mittal, et al., Honorable Mention

​

2024

• Generalization in Diffusion Models Arises from Geometry-Adaptive Harmonic Representations, Zahra Kadkhodaie, Florentin Guth, et al., Outstanding Paper
• Learning Interactive Real-World Simulators, Sherry Yang, Yilun Du, et al., Outstanding Paper
• Vision Transformers Need Registers, Timothee Darcet, Maxime Oquab, et al., Outstanding Paper
• Protein Discovery with Discrete Walk-Jump Sampling, Nathan C. Frey, Dan Berenberg, et al., Outstanding Paper

​

2023

• DreamFusion: Text-to-3D using 2D Diffusion, Ben Poole, Ajay Jain, et al., Outstanding Paper
• Emergence of Maps in the Memories of Blind Navigation Agents, Erik Wijmans, Manolis Savva, et al., Outstanding Paper
• Rethinking the Expressive Power of GNNs via Graph Biconnectivity, Bohang Zhang, Shengjie Luo, et al., Outstanding Paper

​

2022

• Efficiently Modeling Long Sequences with Structured State Spaces (S4), Albert Gu, Karan Goel, Christopher Re, Outstanding Paper
• Analytic-DPM: An Analytic Estimate of the Optimal Reverse Variance in Diffusion Models, Fan Bao, Chongxuan Li, et al., Outstanding Paper
• Neural Collapse Under MSE Loss, X.Y. Han, Vardan Papyan, David L. Donoho, Outstanding Paper

​

2021

• Score-Based Generative Modeling through Stochastic Differential Equations, Yang Song, Jascha Sohl-Dickstein, et al., Outstanding Paper
• Learning Mesh-Based Simulation with Graph Networks, Tobias Pfaff, Meire Fortunato, et al., Outstanding Paper
• EigenGame: PCA as a Nash Equilibrium, Ian Gemp, Brian McWilliams, et al., Outstanding Paper

​

2025

• CollabLLM: From Passive Responders to Active Collaborators, Shirley Wu, Michel Galley, et al., Outstanding Paper
• Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusions, Jaeyeon Kim, Kulin Shah, et al., Outstanding Paper
• Roll the Dice & Look Before You Leap: Going Beyond the Creative Limits of Next-Token Prediction, Vaishnavh Nagarajan, Chen Wu, et al., Outstanding Paper
• Score Matching with Missing Data, Josh Givens, Song Liu, Henry Reeve, Outstanding Paper
• Conformal Prediction as Bayesian Quadrature, Jake Snell, Thomas Griffiths, Outstanding Paper

​

2024

• Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution, Aaron Lou, Chenlin Meng, Stefano Ermon, Best Paper
• Considerations for Differentially Private Learning with Large-Scale Public Pretraining, Florian Tramer, Gautam Kamath, Nicholas Carlini, Best Paper

​

2023

• Learning-Rate-Free Learning by D-Adaptation, Aaron Defazio, Konstantin Mishchenko, Outstanding Paper
• A Watermark for Large Language Models, John Kirchenbauer, Jonas Geiping, et al., Outstanding Paper
• Adapting to Game Trees in Zero-Sum Imperfect Information Games, Come Fiegel, Pierre Menard, et al., Outstanding Paper

​

2022

• Understanding Dataset Difficulty with V-Usable Information, Kawin Ethayarajh, Yejin Choi, Swabha Swayamdipta, Outstanding Paper
• Monarch: Expressive Structured Matrices for Efficient and Accurate Training, Tri Dao, et al., Outstanding Paper
• Learning Inverse Folding from Millions of Predicted Structures, Chloe Hsu, Robert Verkuil, et al., Outstanding Paper

​

2021

• Understanding Self-Supervised Learning Dynamics without Contrastive Pairs, Yuandong Tian, Xinlei Chen, Surya Ganguli, Outstanding Paper
• Oops I Took A Gradient: Scalable Sampling for Discrete Distributions, Will Grathwohl, Kevin Swersky, et al., Outstanding Paper

​

2024

• Online Combinatorial Optimization with Group Fairness Constraints, Negin Golrezaei, Rad Niazadeh, et al., Distinguished Paper
• Online Learning of Capacity-Based Preference Models, Margot Herin, Patrice Perny, Nataliya Sokolovska, Distinguished Paper

​

2023

• Levin Tree Search with Context Models, Laurent Orseau, Marcus Hutter, Levi H. S. Lelis, Distinguished Paper
• SAT-Based PAC Learning of Description Logic Concepts, Balder ten Cate, Maurice Funk, et al., Distinguished Paper

​

2022

• Plurality Veto: A Simple Voting Rule Achieving Optimal Metric Distortion, Fatih Kizilkaya, David Kempe, Distinguished Paper

​

2021

• Learning Generalized Unsolvability Heuristics for Classical Planning, Simon Stahlberg, Guillem Frances, Jendrik Seipp, Distinguished Paper

​

2025

• Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond), Liwei Jiang, Yuanjun Chai, et al., Best Paper
• Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free, Zihan Qiu, Zekun Wang, et al. (Alibaba Qwen), Best Paper
• 1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities, Michal Bortkiewicz, et al., Best Paper
• Why Diffusion Models Don’t Memorize: The Role of Implicit Dynamical Regularization, Tony Bonnaire, Raphael Urfin, et al., Best Paper
• Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?, Yang Yue, Zhiqi Chen, et al., Best Paper Runner-Up
• Superposition Yields Robust Neural Scaling, Yizhou Liu, Ziming Liu, Jeff Gore, Best Paper Runner-Up

​

2024

• Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction, Keyu Tian, Yi Jiang, et al., Best Paper
• Stochastic Taylor Derivative Estimator: Efficient Amortization for Arbitrary Differential Operators, Zekun Shi, Zheyuan Hu, et al., Best Paper
• Rho-1: Not All Tokens Are What You Need, Zhenghao Lin, Zhibin Gou, et al., Best Paper Runner-Up
• Guiding a Diffusion Model with a Bad Version of Itself, Tero Karras, Miika Aittala, et al., Best Paper Runner-Up
• The PRISM Alignment Dataset, Hannah Rose Kirk, et al., Best Paper (Datasets & Benchmarks)

​

2023

• Are Emergent Abilities of Large Language Models a Mirage?, Rylan Schaeffer, Brando Miranda, Sanmi Koyejo, Outstanding Paper
• Privacy Auditing with One (1) Training Run, Thomas Steinke, Milad Nasr, Matthew Jagielski, Outstanding Paper
• Direct Preference Optimization: Your Language Model is Secretly a Reward Model, Rafael Rafailov, et al., Outstanding Paper Runner-Up
• Scaling Data-Constrained Language Models, Niklas Muennighoff, et al., Outstanding Paper Runner-Up
• DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models, Boxin Wang, et al., Outstanding Benchmark Paper

​

2022

• Elucidating the Design Space of Diffusion-Based Generative Models, Tero Karras, Miika Aittala, et al., Outstanding Paper
• Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding (Imagen), Chitwan Saharia, et al. (Google Brain), Outstanding Paper
• Is Out-of-distribution Detection Learnable?, Zhen Fang, Yixuan Li, et al., Outstanding Paper
• Gradient Descent: The Ultimate Optimizer, Kartik Chandra, Audrey Xie, et al., Outstanding Paper

​

2021

• A Universal Law of Robustness via Isoperimetry, Sebastien Bubeck, Mark Sellke, Outstanding Paper
• Deep Reinforcement Learning at the Edge of the Statistical Precipice, Rishabh Agarwal, Max Schwarzer, et al., Outstanding Paper
• MAUVE: Measuring the Gap Between Neural Text and Human Text, Krishna Pillutla, Swabha Swayamdipta, et al., Outstanding Paper