ICML 2025 Poster Papers
2,794 papers found • Page 1 of 56
$\infty$-Video: A Training-Free Approach to Long Video Understanding via Continuous-Time Memory Consolidation
Saúl Santos, António Farinhas, Daniel McNamee et al.
$S^2$FGL: Spatial Spectral Federated Graph Learning
Zihan Tan, Suyuan Huang, Guancheng Wan et al.
$\texttt{I$^2$MoE}$: Interpretable Multimodal Interaction-aware Mixture-of-Experts
Jiayi Xin, Sukwon Yun, Jie Peng et al.
3D-LMVIC: Learning-based Multi-View Image Compression with 3D Gaussian Geometric Priors
Yujun Huang, Bin Chen, Niu Lian et al.
3D Question Answering via only 2D Vision-Language Models
FENGYUN WANG, Sicheng Yu, Jiawei Wu et al.
AAAR-1.0: Assessing AI’s Potential to Assist Research
Renze Lou, Hanzi Xu, Sijia Wang et al.
A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
Michael Munn, Susan Wei
Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
Shengbin Ye, Meng Li
ABNet: Adaptive explicit-Barrier Net for Safe and Scalable Robot Learning
Wei Xiao, Johnson Tsun-Hsuan Wang, Chuang Gan et al.
A Bregman Proximal Viewpoint on Neural Operators
Abdel-Rahim Mezidi, Jordan Patracone, Saverio Salzo et al.
A Causal World Model Underlying Next Token Prediction: Exploring GPT in a Controlled Environment
Raanan Yehezkel Rohekar, Yaniv Gurwicz, Sungduk Yu et al.
Accelerated Diffusion Models via Speculative Sampling
Valentin De Bortoli, Alexandre Galashov, Arthur Gretton et al.
Accelerating Large Language Model Reasoning via Speculative Search
Zhihai Wang, Jie Wang, Jilai Pan et al.
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck et al.
Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
Ze Cheng, Zhuoyu Li, Wang Xiaoqiang et al.
Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach
Yang Xu, Vaneet Aggarwal
Accelerating Spectral Clustering under Fairness Constraints
Francesco Tonin, Alex Lambert, Johan Suykens et al.
Accelerating Unbiased LLM Evaluation via Synthetic Feedback
Zhaoyi Zhou, Yuda Song, Andrea Zanette
Accurate and Efficient World Modeling with Masked Latent Transformers
Maxime Burchi, Radu Timofte
Accurate Identification of Communication Between Multiple Interacting Neural Populations
Belle Liu, Jacob I Sacks, Matthew Golub
A Certified Unlearning Approach without Access to Source Data
Umit Basaran, Sk Miraj Ahmed, Amit Roy-Chowdhury et al.
A Classification View on Meta Learning Bandits
Mirco Mutti, Jeongyeol Kwon, Shie Mannor et al.
A Closer Look at Backdoor Attacks on CLIP
Shuo He, Zhifang Zhang, Feng Liu et al.
A Closer Look at Generalized BH Algorithm for Out-of-Distribution Detection
Xinsong Ma, Jie Wu, Weiwei Liu
A Closer Look at Transformers for Time Series Forecasting: Understanding Why They Work and Where They Struggle
Yu Chen, Nathalia Céspedes, Payam Barnaghi
A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
Varshita Kolipaka, Akshit Sinha, Debangan Mishra et al.
A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD
Ruinan Jin, Xiao Li, Yaoliang Yu et al.
A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
Kihyuk Hong, Ambuj Tewari
A Cross Modal Knowledge Distillation & Data Augmentation Recipe for Improving Transcriptomics Representations through Morphological Features
Ihab Bendidi, Yassir El Mesbahi, Alisandra Denton et al.
Action-Constrained Imitation Learning
Chia-Han Yeh, Tse-Sheng Nan, Risto Vuorio et al.
Action-Dependent Optimality-Preserving Reward Shaping
Grant Forbes, Jianxun Wang, Leonardo Villalobos-Arias et al.
Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss
Sangyeon Park, Isaac Han, Seungwon Oh et al.
Activation Space Interventions Can Be Transferred Between Large Language Models
Narmeen Oozeer, Dhruv Nathawani, Nirmalendu Prakash et al.
Active Evaluation Acquisition for Efficient LLM Benchmarking
Yang Li, Jie Ma, Miguel Ballesteros et al.
Active feature acquisition via explainability-driven ranking
Osman Berke Guney, Ketan Saichandran, Karim Elzokm et al.
Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations
Jason Qin, Hans-Hermann Wessels, Carlos Fernandez-Granda et al.
Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
Erica Zhang, Fangzhao Zhang, Mert Pilanci
Active Learning with Selective Time-Step Acquisition for PDEs
Yegon Kim, Hyunsu Kim, Gyeonghoon Ko et al.
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.
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 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.