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NeurIPS
NeurIPS Best Papers
Neural Information Processing Systems
37 papers · 2020–2025
← NeurIPS Conference Info
🏆
2025
(7)
Best Paper Award
Optimal Mistake Bounds for Transductive Online Learning
Zachary Chase, Steve Hanneke, Jonathan Shafer, Shay Moran
Online Algorithms
Best Paper Award
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Yang Yue, Zhiqi Chen, Rui Lu, Andrew Zhao, Zhaokai Wang, Yang Yue, Shiji Song, Gao Huang
LLM
Reinforcement Learning
Reasoning
Best Paper Award
Superposition Yields Robust Neural Scaling
Yizhou Liu, Ziming Liu, Jeff Gore
Robustness
Scalability
Best Paper Award
Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)
Liwei Jiang, Yuanjun Chai, Margaret Li, Mickel Liu, Raymond Fok, Nouha Dziri, Yulia Tsvetkov, Maarten Sap
Best Paper Award
1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities
Kevin Wang, Ishaan Javali, Michał Bortkiewicz, Tomasz Trzciński, Benjamin Eysenbach
Reinforcement Learning
Self-Supervised Learning
Scalability
Best Paper Award
Why Diffusion Models Don’t Memorize: The Role of Implicit Dynamical Regularization in Training
Tony Bonnaire, Raphaël Urfin, Giulio Biroli, Marc Mézard
Best Paper Award
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free
Zihan Qiu, Zekun Wang, Bo Zheng, Zeyu Huang, Kaiyue Wen, Songlin Yang, Rui Men, Le Yu
LLM
🏆
2024
(5)
Best Paper Award
Stochastic Taylor Derivative Estimator: Efficient Amortization for Arbitrary Differential Operators
Li et al.
Optimization
Scientific ML
Best Paper Award
Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction
Tian et al.
Image Generation
Autoregressive
Best Paper Award
The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models
Hannah Rose Kirk, Alexander Whitefield, Paul Röttger, Andrew Bean, Katerina Margatina, Rafael Mosquera, Juan Ciro, Max Bartolo
LLM
Participatory Design
Best Paper Award
Not All Tokens Are What You Need for Pretraining
Zhenghao Lin, Zhibin Gou, Yeyun Gong, Xiao Liu, Yelong Shen, Ruochen Xu, Chen Lin, Yujiu Yang
Best Paper Award
Guiding a Diffusion Model with a Bad Version of Itself
Tero Karras, Miika Aittala, Tuomas Kynkäänniemi, Jaakko Lehtinen, Timo Aila, Samuli Laine
Diffusion Models
🏆
2023
(2)
Best Paper Award
Are Emergent Abilities of Large Language Models a Mirage?
Schaeffer, Miranda & Koyejo
LLM
Emergent Abilities
Best Paper Award
Privacy Auditing with One (1) Training Run
Steinke, Nasr & Jagielski
Privacy
Auditing
🏆
2022
(12)
Best Paper Award
Is Out-of-distribution Detection Learnable?
Fang et al.
OOD Detection
Theory
Best Paper Award
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
Saharia et al.
Imagen
Diffusion
Best Paper Award
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
Generative Models
Best Paper Award
ProcTHOR: Large-Scale Embodied AI Using Procedural Generation
Matt Deitke, Eli VanderBilt, Alvaro Herrasti, Luca Weihs, Jordi Salvador, Kiana Ehsani, Winson Han, Eric Kolve
Generative Models
Scalability
Embodied Interaction
Best Paper Award
Using natural language and program abstractions to instill human inductive biases in machines
Sreejan Kumar, Carlos G Correa, Ishita Dasgupta, Raja Marjieh, Michael Hu, Robert D. Hawkins, Jonathan Cohen, Nathaniel Daw
Best Paper Award
A Neural Corpus Indexer for Document Retrieval
Yujing Wang, Yingyan Hou, Haonan Wang, Ziming Miao, Shibin Wu, Hao Sun, Qi Chen, Yuqing Xia
Best Paper Award
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling
Gerard Ben Arous, Reza Gheissari, Aukosh Jagannath
Scalability
Best Paper Award
Riemannian Score-Based Generative Modelling
Valentin De Bortoli, Emile Mathieu, Michael John Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet
Diffusion Models
Generative Models
Best Paper Award
Gradient Estimation with Discrete Stein Operators
Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis Titsias, Lester Mackey
Optimization
Best Paper Award
An empirical analysis of compute-optimal large language model training
Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de las Casas, Lisa Anne Hendricks
LLM
Language Models
Best Paper Award
Beyond neural scaling laws: beating power law scaling via data pruning
Ben Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, Ari S. Morcos
Scalability
Model Pruning
Best Paper Award
On-Demand Sampling: Learning Optimally from Multiple Distributions
Nika Haghtalab, Michael Jordan, Eric Zhao
🏆
2021
(8)
Outstanding Paper Award
A Universal Law of Robustness via Isoperimetry
Sebastien Bubeck, Mark Sellke
robustness
overparameterization
theory
Outstanding Paper Award
Deep Reinforcement Learning at the Edge of the Statistical Precipice
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron Courville, Marc G. Bellemare
reinforcement learning
evaluation
reproducibility
Outstanding Paper Award
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers
Krishna Pillutla, Swabha Swayamditta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaid Harchaoui
NLP
text generation
evaluation
Outstanding Paper Award
Moser Flow: Divergence-based Generative Modeling on Manifolds
Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman
generative models
manifold learning
Outstanding Paper Award
On the Expressivity of Markov Reward
David Abel, Will Dabney, Anna Harutyunyan, Mark K. Ho, Michael Littman, Doina Precup, Satinder Singh
reinforcement learning
reward modeling
Best Paper Award
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms
Mathieu Even, Raphaël Berthier, Francis Bach, Nicolas Flammarion, Pierre Gaillard, Hadrien Hendrikx, Laurent Massoulié, Adrien Taylor
Optimization
Best Paper Award
Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research
Bernard Koch, Emily Denton, Alex Hanna, Jacob Gates Foster
Best Paper Award
ATOM3D: Tasks on Molecules in Three Dimensions
Raphael John Lamarre Townshend, Martin Vögele, Patricia Adriana Suriana, Alexander Derry, Alexander Powers, Yianni Laloudakis, Sidhika Balachandar, Bowen Jing
🏆
2020
(3)
Best Paper Award
No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium
Andrea Celli, Alberto Marchesi, Gabriele Farine, Nicola Gatti
Best Paper Award
Improved guarantees and a multiple-descent curve for the Column Subset Selection Problem and the Nyström method
Michal Derezinski, Rajiv Khanna, Michael W. Mahoney
Best Paper Award
Language Models are Few-Shot Learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D. Kaplan
Few-Shot Learning