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NeurIPS

AI/ML마감

Neural Information Processing Systems

📍 Sydney, Australia · 2026-12-06 ~ 2026-12-12

공식 웹사이트DBLP정보 오류 신고
채택률22.9%(2024, 3,584/15,671)
키워드ComplexityLLM

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데드라인

2026 (main)
📍 Sydney, Australia
📋 Abstract: 2026-05-04
📝 Paper: 2026-05-06
📬 Notification: 2026-09-24
📅 학회: 2026-12-06 ~ 2026-12-12

데드라인은 변경될 수 있습니다. 제출 전 공식 웹사이트에서 최종 일정을 확인하세요.

Acceptance Rate?

연도제출채택채택률
20209,4671,90320.1%
20219,1222,34425.7%
202210,4112,67225.6%
202312,3433,21826.1%
202415,6713,58422.9%

Research Trend?

Best Papers

🏆 2025Best Paper Award
Optimal Mistake Bounds for Transductive Online Learning
Zachary Chase, Steve Hanneke, Jonathan Shafer, Shay Moran
Online Algorithms
🏆 2025Best 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
LLMReinforcement LearningReasoning
🏆 2025Best Paper Award
Superposition Yields Robust Neural Scaling
Yizhou Liu, Ziming Liu, Jeff Gore
RobustnessScalability
🏆 2025Best 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
🏆 2025Best 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 LearningSelf-Supervised LearningScalability
🏆 2025Best Paper Award
Why Diffusion Models Don’t Memorize: The Role of Implicit Dynamical Regularization in Training
Tony Bonnaire, Raphaël Urfin, Giulio Biroli, Marc Mézard
🏆 2025Best 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
🏆 2024Best Paper Award
Stochastic Taylor Derivative Estimator: Efficient Amortization for Arbitrary Differential Operators
Li et al.
OptimizationScientific ML
🏆 2024Best Paper Award
Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction
Tian et al.
Image GenerationAutoregressive
🏆 2024Best 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
LLMParticipatory Design
🏆 2024Best 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
🏆 2024Best 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
🏆 2023Best Paper Award
Are Emergent Abilities of Large Language Models a Mirage?
Schaeffer, Miranda & Koyejo
LLMEmergent Abilities
🏆 2023Best Paper Award
Privacy Auditing with One (1) Training Run
Steinke, Nasr & Jagielski
PrivacyAuditing
🏆 2022Best Paper Award
Is Out-of-distribution Detection Learnable?
Fang et al.
OOD DetectionTheory
🏆 2022Best Paper Award
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
Saharia et al.
ImagenDiffusion
🏆 2022Best Paper Award
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
Generative Models
🏆 2022Best 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
🏆 2022Best 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
🏆 2022Best 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
🏆 2022Best Paper Award
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling
Gerard Ben Arous, Reza Gheissari, Aukosh Jagannath
Scalability
🏆 2022Best 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
🏆 2022Best Paper Award
Gradient Estimation with Discrete Stein Operators
Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis Titsias, Lester Mackey
Optimization
🏆 2022Best 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
🏆 2022Best 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
🏆 2022Best Paper Award
On-Demand Sampling: Learning Optimally from Multiple Distributions
Nika Haghtalab, Michael Jordan, Eric Zhao
🏆 2021Outstanding Paper Award
A Universal Law of Robustness via Isoperimetry
Sebastien Bubeck, Mark Sellke
robustnessoverparameterizationtheory
🏆 2021Outstanding 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
🏆 2021Outstanding 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
🏆 2021Outstanding Paper Award
Moser Flow: Divergence-based Generative Modeling on Manifolds
Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman
generative modelsmanifold learning
🏆 2021Outstanding 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
🏆 2021Best 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
🏆 2021Best Paper Award
Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research
Bernard Koch, Emily Denton, Alex Hanna, Jacob Gates Foster
🏆 2021Best 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
🏆 2020Best Paper Award
No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium
Andrea Celli, Alberto Marchesi, Gabriele Farine, Nicola Gatti
🏆 2020Best 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
🏆 2020Best 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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