International Conference on Machine Learning
ICML
A*
CORE rank
CORE rank (raw)
A*
Acceptance rate
27.5% (2024)
Fields of research
Machine Learning
Papers indexed
17,065
1988–2025
Papers per year
19883,341 peak2025
Most published authors
ICML papers
17,065 records sourced from DBLP. Search titles, filter by year, sort by recency.
| Year | Title | Authors |
|---|---|---|
| 2025 | Emergence and Effectiveness of Task Vectors in In-Context Learning: An Encoder Decoder Perspective. | Seungwook Han, Jinyeop Song, Jeff Gore, Pulkit Agrawal |
| 2025 | Learnings from Scaling Visual Tokenizers for Reconstruction and Generation. | Philippe Hansen-Estruch, David Yan, Ching-Yao Chuang, Orr Zohar, Jialiang Wang, Tingbo Hou, Tao Xu, Sriram Vishwanath, Peter Vajda, Xinlei Chen |
| 2025 | Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence. | Yinbin Han, Meisam Razaviyayn, Renyuan Xu |
| 2025 | Efficient Optimization with Orthogonality Constraint: a Randomized Riemannian Submanifold Method. | Andi Han, Pierre-Louis Poirion, Akiko Takeda |
| 2025 | Position: General Intelligence Requires Reward-based Pretraining. | Seungwook Han, Jyothish Pari, Samuel J. Gershman, Pulkit Agrawal |
| 2025 | Ranked Entropy Minimization for Continual Test-Time Adaptation. | Jisu Han, Jaemin Na, Wonjun Hwang |
| 2025 | A Trichotomy for List Transductive Online Learning. | Steve Hanneke, Amirreza Shaeiri |
| 2025 | Representation Preserving Multiclass Agnostic to Realizable Reduction. | Steve Hanneke, Qinglin Meng, Amirreza Shaeiri |
| 2025 | Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images? | Yujin Han, Andi Han, Wei Huang, Chaochao Lu, Difan Zou |
| 2025 | Of Mice and Machines: A Comparison of Learning Between Real World Mice and RL Agents. | Shuo Han, German Espinosa, Junda Huang, Daniel A. Dombeck, Malcolm A. MacIver, Bradly C. Stadie |
| 2025 | On the Role of Label Noise in the Feature Learning Process. | Andi Han, Wei Huang, Zhanpeng Zhou, Gang Niu, Wuyang Chen, Junchi Yan, Akiko Takeda, Taiji Suzuki |
| 2025 | Quantifying Prediction Consistency Under Fine-tuning Multiplicity in Tabular LLMs. | Faisal Hamman, Pasan Dissanayake, Saumitra Mishra, Freddy Lcu, Sanghamitra Dutta |
| 2025 | Hierarchical Refinement: Optimal Transport to Infinity and Beyond. | Peter Halmos, Julian Gold, Xinhao Liu, Benjamin J. Raphael |
| 2025 | Proactive Agents for Multi-Turn Text-to-Image Generation Under Uncertainty. | Meera Hahn, Wenjun Zeng, Nithish Kannen, Rich Galt, Kartikeya Badola, Been Kim, Zi Wang |
| 2025 | Learning Extrapolative Sequence Transformations from Markov Chains. | Sophia Hager, Aleem Khan, Andrew Wang, Nicholas Andrews |
| 2025 | Predicting the Susceptibility of Examples to Catastrophic Forgetting. | Guy Hacohen, Tinne Tuytelaars |
| 2025 | Limitations of measure-first protocols in quantum machine learning. | Casper Gyurik, Riccardo Molteni, Vedran Dunjko |
| 2025 | Exponential Family Variational Flow Matching for Tabular Data Generation. | Andrs Guzmn-Cordero, Floor Eijkelboom, Jan-Willem van de Meent |
| 2025 | From RAG to Memory: Non-Parametric Continual Learning for Large Language Models. | Bernal Jimnez Gutirrez, Yiheng Shu, Weijian Qi, Sizhe Zhou, Yu Su |
| 2025 | Guardians of Image Quality: Benchmarking Defenses Against Adversarial Attacks on Image Quality Metrics. | Aleksandr Gushchin, Khaled Abud, Georgii Bychkov, Ekaterina Shumitskaya, Anna Chistyakova, Sergey Lavrushkin, Bader Rasheed, Kirill Malyshev, Dmitriy S. Vatolin, Anastasia Antsiferova |
| 2025 | Inverse Bridge Matching Distillation. | Nikita Gushchin, David Li, Daniil Selikhanovych, Evgeny Burnaev, Dmitry Baranchuk, Alexander Korotin |
| 2025 | HiRemate: Hierarchical Approach for Efficient Re-materialization of Neural Networks. | Julia Gusak, Xunyi Zhao, Thotime Le Hellard, Zhe Li, Lionel Eyraud-Dubois, Olivier Beaumont |
| 2025 | PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity. | Mustafa Burak Gurbuz, Xingyu Zheng, Constantine Dovrolis |
| 2025 | AlphaPO: Reward Shape Matters for LLM Alignment. | Aman Gupta, Shao Tang, Qingquan Song, Sirou Zhu, Jiwoo Hong, Ankan Saha, Viral Gupta, Noah Lee, Eunki Kim, Siyu Zhu, Parag Agrawal, Natesh S. Pillai, S. Sathiya Keerthi |
| 2025 | AMPO: Active Multi Preference Optimization for Self-play Preference Selection. | Taneesh Gupta, Rahul Madhavan, Xuchao Zhang, Chetan Bansal, Saravan Rajmohan |
2,226–2,250 of 17,065← PreviousNext →
Comparable venues
Other A*/A conferences filed under the same field of research.
- A*ICLRInternational Conference on Learning Representations
- AAISTATSInternational Conference on Artificial Intelligence and Statistics
- A*COLTConference on Learning Theory
- APPSNParallel Problem Solving from Nature
- AECML PKDDEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (PKDD and ECML combined from 2008)
- A*NeurIPSAdvances in Neural Information Processing Systems (was NIPS)