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ICML

AI/ML마감

International Conference on Machine Learning

📍 Seoul, Korea · 2026-07-06 ~ 2026-07-11

공식 웹사이트DBLP정보 오류 신고
채택률27.5%(2024, 2,609/9,473)
키워드Reinforcement LearningGenerativeAlignmentPolicy OptimizationOptimization

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데드라인

2026 (main)
📍 Seoul, Korea
📋 Abstract: 2026-01-23
📝 Paper: 2026-01-28
📬 Notification: 2026-04-30
📅 학회: 2026-07-06 ~ 2026-07-11

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

Acceptance Rate?

연도제출채택채택률
20204,9901,08821.8%
20215,5131,18421.5%
20225,6301,23521.9%
20236,5381,82727.9%
20249,4732,60927.5%

Research Trend?

Best Papers

🏆 2026Outstanding Paper Award
The Flexibility Trap: Rethinking the Value of Arbitrary Order in Diffusion Language Models
Zanlin Ni, Shenzhi Wang, Yang Yue, Tianyu Yu, Weilin Zhao, Yeguo Hua, Tianyi Chen, Jun Song, Cheng Yu, Bo Zheng, Gao Huang
Diffusion Language ModelsReinforcement Learning
🏆 2026Outstanding Paper Award
High-Accuracy Sampling for Diffusion Models and Log-Concave Distributions
Fan Chen, Sinho Chewi, Constantinos Daskalakis, Alexander Rakhlin
Diffusion ModelsSampling Theory
🏆 2026Outstanding Paper Award
Position: The Alignment Community is Unintentionally Building a Censor’s Toolkit
Sarah Ball, Phil Hackemann
Position PaperAI Alignment
🏆 2026Honorable Mention
The Obfuscation Atlas: Mapping Where Honesty Emerges in RLVR with Deception Probes
Mohammad Taufeeque, Stefan Heimersheim, Adam Gleave, Chris Cundy
RLVRAI Alignment
🏆 2026Honorable Mention
Motion Attribution for Video Generation
Xindi Wu, Despoina Paschalidou, Jun Gao, Antonio Torralba, Laura Leal-Taixé, Olga Russakovsky, Sanja Fidler, Jonathan Lorraine
Video GenerationData Attribution
🏆 2026Honorable Mention
How much can language models memorize?
John Xavier Morris, Chawin Sitawarin, Narine Kokhlikyan, Chuan Guo, G. Edward Suh, Alexander M Rush, Kamalika Chaudhuri, Saeed Mahloujifar
Language ModelsMemorization
🏆 2026Honorable Mention
A Random Matrix Perspective on the Consistency of Diffusion Models
Binxu Wang, Jacob A Zavatone-Veth, Cengiz Pehlevan
Diffusion ModelsRandom Matrix Theory
🏆 2026Honorable Mention
To Grok Grokking: Provable Grokking in Ridge Regression
Mingyue Xu, Gal Vardi, Itay Safran
GrokkingTheory
🏆 2026Honorable Mention
Position: AI/ML Deepfake Research is Misaligned with AI Generated Non-Consensual Intimate Imagery (AIG-NCII)
Li Qiwei, Wells Lucas Santo, Sarita Schoenebeck, Eric Gilbert
Position PaperDeepfakesAI Safety
🏆 2026Test of Time Award
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu
Reinforcement LearningAsynchronous Learning
🏆 2025Outstanding Paper Award
CollabLLM: From Passive Responders to Active Collaborators
Wu, Galley, Peng, Cheng, Li, Dou, Cai, Zou, Leskovec, Gao
LLMAgent
🏆 2025Outstanding Paper Award
Conformal Prediction as Bayesian Quadrature
Snell, Griffiths
Conformal PredictionBayesian
🏆 2025Outstanding Paper Award
Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction
Nagarajan, Wu, Ding, Raghunathan
LLMGeneration
🏆 2025Outstanding Paper Award
Score Matching with Missing Data
Givens, Liu, Reeve
Generative ModelStatistics
🏆 2025Outstanding Paper Award
The Value of Prediction in Identifying the Worst-Off
Fischer Abaigar, Kern, Perdomo
FairnessPrediction
🏆 2025Outstanding Paper Award
Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusions
Kim, Shah, Kontonis, Kakade, Chen
DiffusionLLM
🏆 2024Best Paper Award
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
Lou, Meng & Ermon
DiffusionDiscrete
🏆 2024Best Paper Award
Position: Measure Dataset Diversity, Don't Just Claim It
Zhao et al.
DatasetsDiversity
🏆 2024Best Paper Award
Scaling Rectified Flow Transformers for High-Resolution Image Synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz
Image GenerationSynthesisScalability
🏆 2024Best Paper Award
VideoPoet: A Large Language Model for Zero-Shot Video Generation
Dan Kondratyuk, Lijun Yu, Xiuye Gu, José Lezama, Jonathan Huang, Grant Schindler, Rachel Hornung, Vighnesh N. Birodkar
LLMZero-Shot LearningLanguage ModelsGenerative Models
🏆 2024Best Paper Award
Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing
Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy
OptimizationTracing
🏆 2024Best Paper Award
Debating with More Persuasive LLMs Leads to More Truthful Answers
Akbir Khan, John Hughes, Dan Valentine, Laura Ruis, Kshitij Sachan, Ansh Radhakrishnan, Edward Grefenstette, Samuel R. Bowman
LLM
🏆 2024Best Paper Award
Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo
Stephen Zhao, Rob Brekelmans, Alireza Makhzani, Roger Grosse
🏆 2024Best Paper Award
Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
Florian Tramèr, Gautam Kamath, Nicholas Carlini
Scalability
🏆 2024Best Paper Award
Genie: Generative Interactive Environments
Jake Bruce, Michael J. Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar
Generative Models
🏆 2024Best Paper Award
Stealing part of a production language model
Nicholas Carlini, Daniel Paleka, Krishnamurthy Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski
Language Models
🏆 2023Best Paper Award
A Watermark for Large Language Models
Kirchenbauer et al.
LLMWatermark
🏆 2023Best Paper Award
Learning-Rate-Free Learning by D-Adaptation
Defazio & Mishchenko
OptimizationLearning Rate
🏆 2023Best Paper Award
Generalization on the Unseen, Logic Reasoning and Degree Curriculum
Emmanuel Abbe, Samy Bengio, Aryo Lotfi, Kevin Rizk
ReasoningLogic
🏆 2023Best Paper Award
Adapting to game trees in zero-sum imperfect information games
Côme Fiegel, Pierre Menard, Tadashi Kozuno, Remi Munos, Vianney Perchet, Michal Valko
🏆 2023Best Paper Award
Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains
Vishwaraj Doshi, Jie Hu, Do Young Eun
Randomized AlgorithmsMarkov Models
🏆 2023Best Paper Award
Bayesian Design Principles for Frequentist Sequential Learning
Yunbei Xu & Assaf Zeevi
Bayesian Methods
🏆 2022Best Paper Award
Understanding Dataset Difficulty with V-Usable Information
Ethayarajh et al.
DatasetInformation Theory
🏆 2022Best Paper Award
Do Differentiable Simulators Give Better Policy Gradients?
Hyung Ju Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake
🏆 2022Best Paper Award
The Importance of Non-Markovianity in Maximum State Entropy Exploration
Mirco Mutti, Riccardo De Santi, Marcello Restelli
Exploration
🏆 2022Best Paper Award
G-Mixup: Graph Data Augmentation for Graph Classification
Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu
Classification
🏆 2022Best Paper Award
Privacy for Free: How does Dataset Condensation Help Privacy?
Tian Dong, Bo Zhao, Lingjuan Lyu
Privacy
🏆 2022Best Paper Award
Stable Conformal Prediction Sets
Eugene Ndiaye
🏆 2022Best Paper Award
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Sanae Lotfi, Pavel Izmailov, Gregory Benton, Micah Goldblum, Andrew Wilson
Bayesian Methods
🏆 2022Best Paper Award
Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation
Jiali Wang, Wen Huang, Rujun Jiang, Xudong Li, Alex Wang
🏆 2022Best Paper Award
Learning Mixtures of Linear Dynamical Systems
Yanxi Chen & H. Vincent Poor
🏆 2022Best Paper Award
Causal Conceptions of Fairness and their Consequences
Hamed Nilforoshan, Johann Gaebler, Ravi Shroff, Sharad Goel
Fairness
🏆 2021Best Paper Award
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies
Paul Vicol, Luke Metz, Jascha Sohl-Dickstein
meta-learninggradient estimationoptimization
🏆 2020Best Paper Award
On Learning Sets of Symmetric Elements
Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
🏆 2020Best Paper Award
Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems
Kiaxuan Wei, Angelica Aviles-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schonlieb, Hua Huang

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