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ICML 2025

A*

International Conference on Machine Learning

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3,342
accepted papers
3,214
authors
July 11-19, 2025
dates
Canada
location

3,342 / 3,342 papers

  1. 1
    "Who experiences large model decay and why?" A Hierarchical Framework for Diagnosing Heterogeneous Performance Drift
    Harvineet Singh
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  2. 2
    "Why Is There a Tumor?": Tell Me the Reason, Show Me the Evidence
    Mengmeng Ma
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  3. 3
    (How) Can Transformers Predict Pseudo-Random Numbers?
    Tao Tao
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  4. 4
    (How) Do Language Models Track State?
    Belinda Z. Li
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  5. 5
    3D Question Answering via only 2D Vision-Language Models
    Fengyun Wang
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  6. 6
    3D-LMVIC: Learning-based Multi-View Image Compression with 3D Gaussian Geometric Priors
    Yujun Huang
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  7. 7
    A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
    Michael Munn
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  8. 8
    A Bregman Proximal Viewpoint on Neural Operators
    Abdel-Rahim Mezidi
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  9. 9
    A Causal World Model Underlying Next Token Prediction: Exploring GPT in a Controlled Environment
    Raanan Yehezkel Rohekar
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  10. 10
    A Certified Unlearning Approach without Access to Source Data
    Umit Yigit Basaran
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  11. 11
    A Chaotic Dynamics Framework Inspired by Dorsal Stream for Event Signal Processing
    Yu Chen
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  12. 12
    A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment
    Edward Y. Chang
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  13. 13
    A Classification View on Meta Learning Bandits
    Mirco Mutti
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  14. 14
    A Closer Look at Backdoor Attacks on CLIP
    Shuo He
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  15. 15
    A Closer Look at Generalized BH Algorithm for Out-of-Distribution Detection
    Xinsong Ma
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  16. 16
    A Closer Look at Multimodal Representation Collapse
    Abhra Chaudhuri
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  17. 17
    A Closer Look at Transformers for Time Series Forecasting: Understanding Why They Work and Where They Struggle
    Yu Chen
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  18. 18
    A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
    Varshita Kolipaka
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  19. 19
    A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD
    Ruinan Jin
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  20. 20
    A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
    Kihyuk Hong
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  21. 21
    A Cross Modal Knowledge Distillation & Data Augmentation Recipe for Improving Transcriptomics Representations through Morphological Features
    Ihab Bendidi
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  22. 22
    A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Attention Networks
    Biswadeep Chakraborty
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  23. 23
    A First-order Generative Bilevel Optimization Framework for Diffusion Models
    Quan Xiao
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  24. 24
    A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control
    Zilin Kang
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  25. 25
    A General Framework for Inference-time Scaling and Steering of Diffusion Models
    Raghav Singhal
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  26. 26
    A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition
    Nian Liu
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  27. 27
    A General Representation-Based Approach to Multi-Source Domain Adaptation
    Ignavier Ng
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  28. 28
    A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments
    Yuchen Wang
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  29. 29
    A Generalization Result for Convergence in Learning-to-Optimize
    Michael Sucker
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  30. 30
    A Generalization Theory for Zero-Shot Prediction
    Ronak Mehta
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  31. 31
    A Generic Family of Graphical Models: Diversity, Efficiency, and Heterogeneity
    Yufei Huang
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  32. 32
    A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings
    Shib Sankar Dasgupta
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  33. 33
    A Hitchhiker's Guide to Scaling Law Estimation
    Leshem Choshen
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  34. 34
    A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks
    Thomas Schmied
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  35. 35
    A Lens into Interpretable Transformer Mistakes via Semantic Dependency
    Ruo-Jing Dong
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  36. 36
    A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
    Shivam Kumar
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  37. 37
    A Machine Learning Approach to Duality in Statistical Physics
    Prateek Gupta
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  38. 38
    A Manifold Perspective on the Statistical Generalization of Graph Neural Networks
    Zhiyang Wang
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  39. 39
    A Market for Accuracy: Classification Under Competition
    Ohad Einav
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  40. 40
    A Mathematical Framework for AI-Human Integration in Work
    L. Elisa Celis
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  41. 41
    A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models
    Yiming Chen
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  42. 42
    A Meta-learner for Heterogeneous Effects in Difference-in-Differences
    Hui Lan
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  43. 43
    A Mixed-Curvature based Pre-training Paradigm for Multi-Task Vehicle Routing Solver
    Suyu Liu
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  44. 44
    A Mixture-Based Framework for Guiding Diffusion Models
    Yazid Janati
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  45. 45
    A Model of Place Field Reorganization During Reward Maximization
    M. Ganesh Kumar
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  46. 46
    A Multi-Region Brain Model to Elucidate the Role of Hippocampus in Spatially Embedded Decision-Making
    Yi Xie
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  47. 47
    A Near Linear Query Lower Bound for Submodular Maximization
    Binghui Peng
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  48. 48
    A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization
    Bokun Wang
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  49. 49
    A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability
    Pouria Fatemi
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  50. 50
    A New Concentration Inequality for Sampling Without Replacement and Its Application for Transductive Learning
    Yingzhen Yang
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