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Best Papers/NeurIPS

NeurIPS Best Papers

Neural Information Processing Systems

27 papers · 2020–2024

← NeurIPS 학회 정보

🏆 2024(2)

Best Paper Award
Stochastic Taylor Derivative Estimator: Efficient Amortization for Arbitrary Differential Operators
Li et al.
OptimizationScientific ML
Best Paper Award
Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction
Tian et al.
Image GenerationAutoregressive

🏆 2023(2)

Best Paper Award
Are Emergent Abilities of Large Language Models a Mirage?
Schaeffer, Miranda & Koyejo
LLMEmergent Abilities
Best Paper Award
Privacy Auditing with One (1) Training Run
Steinke, Nasr & Jagielski
PrivacyAuditing

🏆 2022(12)

Best Paper Award
Is Out-of-distribution Detection Learnable?
Fang et al.
OOD DetectionTheory
Best Paper Award
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
Saharia et al.
ImagenDiffusion
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 ModelsScalabilityEmbodied 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 ModelsGenerative 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
LLMLanguage 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
ScalabilityModel 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
robustnessoverparameterizationtheory
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 learningevaluationreproducibility
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
NLPtext generationevaluation
Outstanding Paper Award
Moser Flow: Divergence-based Generative Modeling on Manifolds
Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman
generative modelsmanifold 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 learningreward 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

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