ICML 2025 Papers
3,340 papers found • Page 2 of 67
Active Reward Modeling: Adaptive Preference Labeling for Large Language Model Alignment
Yunyi Shen, Hao Sun, Jean-Francois Ton
Active Treatment Effect Estimation via Limited Samples
Zhiheng Zhang, Haoxiang Wang, Haoxuan Li et al.
Actor-Critics Can Achieve Optimal Sample Efficiency
Kevin Tan, Wei Fan, Yuting Wei
AdaDecode: Accelerating LLM Decoding with Adaptive Layer Parallelism
Zhepei Wei, Wei-Lin Chen, Xinyu Zhu et al.
Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
Jintao Tong, Ran Ma, Yixiong Zou et al.
Adapting Precomputed Features for Efficient Graph Condensation
Yuan Li, Jun Hu, Zemin Liu et al.
Adapting to Evolving Adversaries with Regularized Continual Robust Training
Sihui Dai, Christian Cianfarani, Vikash Sehwag et al.
Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning
Erchi Wang, Yuqing Zhu, Yu-Xiang Wang
Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation
Bohan Lyu, Yadi Cao, Duncan Watson-Parris et al.
Adaptive Data Collection for Robust Learning Across Multiple Distributions
Chengbo Zang, Mehmet Turkcan, Gil Zussman et al.
Adaptive Elicitation of Latent Information Using Natural Language
Jimmy Wang, Tom Zollo, Richard Zemel et al.
Adaptive Estimation and Learning under Temporal Distribution Shift
Dheeraj Baby, Yifei Tang, Hieu Nguyen et al.
Adaptive Exploration for Multi-Reward Multi-Policy Evaluation
Alessio Russo, Aldo Pacchiano
Adaptive Flow Matching for Resolving Small-Scale Physics
Stathi Fotiadis, Noah Brenowitz, Tomas Geffner et al.
Adaptive kernel predictors from feature-learning infinite limits of neural networks
Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan
Adaptive Learn-then-Test: Statistically Valid and Efficient Hyperparameter Selection
Matteo Zecchin, Sangwoo Park, Osvaldo Simeone
Adaptive Localization of Knowledge Negation for Continual LLM Unlearning
Abudukelimu Wuerkaixi, Qizhou Wang, Sen Cui et al.
Adaptive Median Smoothing: Adversarial Defense for Unlearned Text-to-Image Diffusion Models at Inference Time
XIAOXUAN HAN, Songlin Yang, Wei Wang et al.
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
Federico Errica, Henrik Christiansen, Viktor Zaverkin et al.
Adaptive Multi-prompt Contrastive Network for Few-shot Out-of-distribution Detection
Xiang Fang, Arvind Easwaran, Blaise Genest
Adaptive Partitioning Schemes for Optimistic Optimization
Raja Sunkara, Ardhendu Tripathy
Adaptive Sample Sharing for Multi Agent Linear Bandits
Hamza Cherkaoui, Merwan Barlier, Igor Colin
Adaptive Self-improvement LLM Agentic System for ML Library Development
Genghan Zhang, Weixin Liang, Olivia Hsu et al.
Adaptive Sensitivity Analysis for Robust Augmentation against Natural Corruptions in Image Segmentation
Laura Zheng, Wenjie Wei, Tony Wu et al.
AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
Yuliang Liu, Junjie Lu, Chaofeng Qu et al.
AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo et al.
AdaSplash: Adaptive Sparse Flash Attention
Nuno Gonçalves, Marcos V. Treviso, Andre Martins
AdaWorld: Learning Adaptable World Models with Latent Actions
Shenyuan Gao, Siyuan Zhou, Yilun Du et al.
ADDQ: Adaptive distributional double Q-learning
Leif Döring, Benedikt Wille, Maximilian Birr et al.
Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization
Emiliano Penaloza, Tianyue Zhang, Laurent Charlin et al.
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts
Lan Li, Da-Wei Zhou, Han-Jia Ye et al.
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration
Antoine Wehenkel, Juan L. Gamella, Ozan Sener et al.
ADHMR: Aligning Diffusion-based Human Mesh Recovery via Direct Preference Optimization
Wenhao Shen, Wanqi Yin, Xiaofeng Yang et al.
Ad-Hoc Human-AI Coordination Challenge
Tin Dizdarevic, Ravi Hammond, Tobias Gessler et al.
Ad Hoc Teamwork via Offline Goal-Based Decision Transformers
Xinzhi Zhang, Hoehi Chan, Deheng Ye et al.
ADIOS: Antibody Development via Opponent Shaping
Sebastian Towers, Aleksandra Kalisz, Philippe Robert et al.
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
Aaron Havens, Benjamin Kurt Miller, Bing Yan et al.
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
Guiomar Pescador-Barrios, Sarah Filippi, Mark van der Wilk
Adjustment for Confounding using Pre-Trained Representations
Rickmer Schulte, David Rügamer, Thomas Nagler
AdvAgent: Controllable Blackbox Red-teaming on Web Agents
Chejian Xu, Mintong Kang, Jiawei Zhang et al.
Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
Davide Sartor, Alberto Sinigaglia, Gian Antonio Susto
Advancing Personalized Learning with Neural Collapse for Long-Tail Challenge
Hanglei Hu, Yingying Guo, Zhikang Chen et al.
Adversarial Combinatorial Semi-bandits with Graph Feedback
Yuxiao Wen
Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets
Wei Liu, Zhongyu Niu, Lang Gao et al.
Adversarial Inception Backdoor Attacks against Reinforcement Learning
Ethan Rathbun, Alina Oprea, Christopher Amato
Adversarial Inputs for Linear Algebra Backends
Jonas Möller, Lukas Pirch, Felix Weissberg et al.
Adversarial Perturbations Are Formed by Iteratively Learning Linear Combinations of the Right Singular Vectors of the Adversarial Jacobian
Thomas Paniagua, Chinmay Savadikar, Tianfu Wu
Adversarial Reasoning at Jailbreaking Time
Mahdi Sabbaghi, Paul Kassianik, George Pappas et al.
Adversarial Robust Generalization of Graph Neural Networks
Chang Cao, Han Li, Yulong Wang et al.
Adversarial Robustness in Two-Stage Learning-to-Defer: Algorithms and Guarantees
Yannis Montreuil, Axel Carlier, Lai Xing Ng et al.