ICML Papers

How Expressive are Knowledge Graph Foundation Models?

Xingyue Huang, Pablo Barcelo, Michael Bronstein et al.

How Far Is Video Generation from World Model: A Physical Law Perspective

Bingyi Kang, Yang Yue, Rui Lu et al.

How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees

Haonan Yuan, Qingyun Sun, Junhua Shi et al.

How Much Can We Forget about Data Contamination?

Sebastian Bordt, Suraj Srinivas, Valentyn Boreiko et al.

How to Evaluate and Mitigate IP Infringement in Visual Generative AI?

Zhenting Wang, Chen Chen, Vikash Sehwag et al.

How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects

Wonkwang Lee, Jongwon Jeong, Taehong Moon et al.

How to set AdamW's weight decay as you scale model and dataset size

Xi Wang, Laurence Aitchison

How to Synthesize Text Data without Model Collapse?

Xuekai Zhu, Daixuan Cheng, Hengli Li et al.

How to Train Your Multi-Exit Model? Analyzing the Impact of Training Strategies

Piotr Kubaty, Bartosz Wójcik, Bartłomiej Krzepkowski et al.

How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias

Ruiquan Huang, Yingbin LIANG, Jing Yang

How Transformers Learn Structured Data: Insights From Hierarchical Filtering

Jerome Garnier-Brun, Marc Mezard, Emanuele Moscato et al.

HPS: Hard Preference Sampling for Human Preference Alignment

Xiandong Zou, Wanyu LIN, Yuchen Li et al.

H-Tuning: Toward Low-Cost and Efficient ECG-based Cardiovascular Disease Detection with Pre-Trained Models

Rushuang Zhou, Yuanting Zhang, Yining Dong

Human-Aligned Image Models Improve Visual Decoding from the Brain

Nona Rajabi, Antonio Ribeiro, Miguel Vasco et al.

Human Body Restoration with One-Step Diffusion Model and A New Benchmark

Jue Gong, Jingkai Wang, Zheng Chen et al.

Human Cognition-Inspired Hierarchical Fuzzy Learning Machine

Junbiao Cui, Qin Yue, Jianqing Liang et al.

Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning

Hongyao Chen, Tianyang Xu, Xiaojun Wu et al.

HybridGS: High-Efficiency Gaussian Splatting Data Compression using Dual-Channel Sparse Representation and Point Cloud Encoder

Qi Yang, Le Yang, Geert Van der Auwera et al.

Hybrid Quantum-Classical Multi-Agent Pathfinding

Thore Gerlach, Loong Kuan Lee, Frederic BARBARESCO et al.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras

Qi Xu, Jie Deng, Jiangrong Shen et al.

HYGMA: Hypergraph Coordination Networks with Dynamic Grouping for Multi-Agent Reinforcement Learning

Chiqiang Liu, Dazi Li

Hyperband-based Bayesian Optimization for Black-box Prompt Selection

Lennart Schneider, Martin Wistuba, Aaron Klein et al.

Hyperbolic-PDE GNN: Spectral Graph Neural Networks in the Perspective of A System of Hyperbolic Partial Differential Equations

Juwei Yue, Haikuo Li, Jiawei Sheng et al.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning

Yiran Wang, Chenshu Liu, Yunfan Li et al.

HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting

Boyuan Li, Yicheng Luo, Zhen Liu et al.

HyperIV: Real-time Implied Volatility Smoothing

Yongxin Yang, Wenqi Chen, Chao Shu et al.

HyperNear: Unnoticeable Node Injection Attacks on Hypergraph Neural Networks

Hyperspherical Normalization for Scalable Deep Reinforcement Learning

Hojoon Lee, Youngdo Lee, Takuma Seno et al.

Hyper-Transforming Latent Diffusion Models

Ignacio Peis, Batuhan Koyuncu, Isabel Valera et al.

HyperTree Planning: Enhancing LLM Reasoning via Hierarchical Thinking

Runquan Gui, Zhihai Wang, Jie Wang et al.

Hypo3D: Exploring Hypothetical Reasoning in 3D

Ye Mao, Weixun Luo, Junpeng Jing et al.

Hypothesis Testing for Generalized Thurstone Models

Anuran Makur, Japneet Singh

IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck

Tian Bian, Yifan Niu, Chaohao Yuan et al.

ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks

Zhiyao Ren, Siyuan Liang, Aishan Liu et al.

Identifiable Object Representations under Spatial Ambiguities

Avinash Kori, Francesca Toni, Ben Glocker

Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations

Zhengming Chen, Yewei Xia, Feng Xie et al.

Identifying and Understanding Cross-Class Features in Adversarial Training

Zeming Wei, Yiwen Guo, Yisen Wang

Identifying biological perturbation targets through causal differential networks

Menghua Wu, Umesh Padia, Sean Murphy et al.

Identifying Causal Direction via Variational Bayesian Compression

Quang-Duy Tran, Bao Duong, Phuoc Nguyen et al.

Identifying Metric Structures of Deep Latent Variable Models

Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi et al.

Identifying Neural Dynamics Using Interventional State Space Models

Amin Nejatbakhsh, Yixin Wang

Idiosyncrasies in Large Language Models

Mingjie Sun, Yida Yin, Zhiqiu (Oscar) Xu et al.

iDPA: Instance Decoupled Prompt Attention for Incremental Medical Object Detection

Huahui Yi, Wei Xu, Ziyuan Qin et al.

IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic

Stefano Viel, Luca Viano, Volkan Cevher

Imagine While Reasoning in Space: Multimodal Visualization-of-Thought

Chengzu Li, Wenshan Wu, Huanyu Zhang et al.

Imitation Learning from a Single Temporally Misaligned Video

William Huey, Yuki (Huaxiaoyue) Wang, Anne Wu et al.

IMPACT: Iterative Mask-based Parallel Decoding for Text-to-Audio Generation with Diffusion Modeling

Kuan Po Huang, Shu-wen Yang, Huy Phan et al.

Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks

Yuhang Cai, Kangjie Zhou, Jingfeng Wu et al.

Implicit degree bias in the link prediction task

Rachith Aiyappa, Xin Wang, Munjung Kim et al.

Implicit Language Models are RNNs: Balancing Parallelization and Expressivity

Mark Schoene, Babak Rahmani, Heiner Kremer et al.