ICML 2024

2,610 papers

Generalization Analysis of Stochastic Weight Averaging with General Sampling

Peng Wang, Li Shen, Zerui Tao, Shuaida He, Dacheng Tao

Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery

Caixing Wang, Ziliang Shen

How to Trace Latent Generative Model Generated Images without Artificial Watermark?

Zhenting Wang, Vikash Sehwag, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas

Proteus: Exploring Protein Structure Generation for Enhanced Designability and Efficiency

Chentong Wang, Yannan Qu, Zhangzhi Peng, Yukai Wang, Hongli Zhu

LLM-Empowered State Representation for Reinforcement Learning

Boyuan Wang, Yun Qu, Yuhang Jiang, Jianzhun Shao, Chang Liu

Efficient Online Set-valued Classification with Bandit Feedback

Zhou Wang, Xingye Qiao

Probabilistic Constrained Reinforcement Learning with Formal Interpretability

Yanran Wang, Qiuchen Qian, David Boyle

A Fine-grained Analysis of Fitted Q-evaluation: Beyond Parametric Models

Jiayi Wang, Zhengling Qi, Raymond K. W. Wong

InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining

Boxin Wang, Wei Ping, Lawrence McAfee, Peng Xu, Bo Li

Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data

Yafei Wang, Bo Pan, Mei Li, Jianya Lu, Lingchen Kong

Pi-DUAL: Using privileged information to distinguish clean from noisy labels

Ke Wang, Guillermo Ortiz-Jimenez, Rodolphe Jenatton, Mark Collier, Efi Kokiopoulou

More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning

Kaiwen Wang, Owen Oertell, Alekh Agarwal, Nathan Kallus, Wen Sun

TroVE: Inducing Verifiable and Efficient Toolboxes for Solving Programmatic Tasks

Zhiruo Wang, Graham Neubig, Daniel Fried

Transforming and Combining Rewards for Aligning Large Language Models

Zihao Wang, Chirag Nagpal, Jonathan Berant, Jacob Eisenstein, Alexander Nicholas D’Amour

Achieving Margin Maximization Exponentially Fast via Progressive Norm Rescaling

Mingze Wang, Zeping Min, Lei Wu

EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs

Haohui Wang, Yuzhen Mao, Yujun Yan, Yaoqing Yang, Jianhui Sun

MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-fit Tests with Autocorrelations

Zhangyu Wang, Gengchen Mai, Krzysztof Janowicz, Ni Lao

A Dual-module Framework for Counterfactual Estimation over Time

Xin Wang, Shengfei Lyu, Lishan Yang, Yibing Zhan, Huanhuan Chen

EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data

Shengjie Wang, Shaohuai Liu, Weirui Ye, Jiacheng You, Yang Gao

A Global Geometric Analysis of Maximal Coding Rate Reduction

Peng Wang, Huikang Liu, Druv Pai, Yaodong Yu, Zhihui Zhu

On Discrete Prompt Optimization for Diffusion Models

Ruochen Wang, Ting Liu, Cho-jui Hsieh, Boqing Gong

Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions

Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Chuan-Sheng Foo, Bryan Kian Hsiang Low

Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning

Xiyu Wang, Baijiong Lin, Daochang Liu, Ying-Cong Chen, Chang Xu

Connecting the Dots: Collaborative Fine-tuning for Black-Box Vision-Language Models

Zhengbo Wang, Jian Liang, Ran He, Zilei Wang, Tieniu Tan

Open Ad Hoc Teamwork with Cooperative Game Theory

Jianhong Wang, Yang Li, yuan zhang, Wei Pan, Samuel Kaski

Graph As Point Set

Xiyuan Wang, Pan Li, Muhan Zhang

An Iterative Min-Min Optimization Method for Sparse Bayesian Learning

Yasen Wang, Junlin Li, Zuogong Yue, Ye Yuan

Visual Transformer with Differentiable Channel Selection: An Information Bottleneck Inspired Approach

Yancheng Wang, Ping Li, Yingzhen Yang

Improving Generalization in Offline Reinforcement Learning via Adversarial Data Splitting

Da Wang, Lin Li, Wei Wei, Qixian Yu, Jianye Hao

Highway Value Iteration Networks

Yuhui Wang, Weida Li, Francesco Faccio, Qingyuan Wu, Jürgen Schmidhuber

Bootstrap AutoEncoders With Contrastive Paradigm for Self-supervised Gaze Estimation

Yaoming Wang, Jin Li, Wenrui Dai, Bowen Shi, XIAOPENG ZHANG

StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization

Shida Wang, Qianxiao Li

MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data

Jian Wang, Xin Lan, Yuxin Tian, Jiancheng Lv

In-context Learning on Function Classes Unveiled for Transformers

Zhijie Wang, Bo Jiang, Shuai Li

Total Variation Floodgate for Variable Importance Inference in Classification

Wenshuo Wang, Lucas Janson, Lihua Lei, Aaditya Ramdas

Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical

Wei Wang, Takashi Ishida, Yu-Jie Zhang, Gang Niu, Masashi Sugiyama

Rapid Learning without Catastrophic Forgetting in the Morris Water Maze

Raymond Wang, Jaedong Hwang, Akhilan Boopathy, Ila R Fiete

Optimal Kernel Choice for Score Function-based Causal Discovery

Wenjie Wang, Biwei Huang, Feng Liu, Xinge You, Tongliang Liu

SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models

Xiaoxuan Wang, Ziniu Hu, Pan Lu, Yanqiao Zhu, Jieyu Zhang

Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution

Rui Wang, Elyssa Hofgard, Han Gao, Robin Walters, Tess Smidt

Mollification Effects of Policy Gradient Methods

Tao Wang, Sylvia Lee Herbert, Sicun Gao

EvGGS: A Collaborative Learning Framework for Event-based Generalizable Gaussian Splatting

Jiaxu Wang, Junhao He, Ziyi Zhang, Mingyuan Sun, Jingkai Sun

Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments

Han Wang, Sihong He, Zhili Zhang, Fei Miao, James Anderson

Understanding Heterophily for Graph Neural Networks

Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang

Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach

Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser

MEMORYLLM: Towards Self-Updatable Large Language Models

Yu Wang, Yifan Gao, Xiusi Chen, Haoming Jiang, Shiyang Li

Optimal Kernel Quantile Learning with Random Features

Caixing Wang, Xingdong Feng

Swallowing the Bitter Pill: Simplified Scalable Conformer Generation

Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Angel Bautista

Monotone, Bi-Lipschitz, and Polyak-Łojasiewicz Networks

Ruigang Wang, Krishnamurthy Dj Dvijotham, Ian Manchester

An Efficient Maximal Ancestral Graph Listing Algorithm

Tian-Zuo Wang, Wen-Bo Du, Zhi-Hua Zhou

Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View

Jin Wang, Shichao Dong, Yapeng Zhu, Kelu Yao, Weidong Zhao

Imitation Learning from Purified Demonstrations

Yunke Wang, Minjing Dong, Yukun Zhao, Bo Du, Chang Xu

Adaptively Learning to Select-Rank in Online Platforms

Jingyuan Wang, Perry Dong, Ying Jin, Ruohan Zhan, Zhengyuan Zhou

Localizing Task Information for Improved Model Merging and Compression

Ke Wang, Nikolaos Dimitriadis, Guillermo Ortiz-Jimenez, Francois Fleuret, Pascal Frossard

TVE: Learning Meta-attribution for Transferable Vision Explainer

Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang

Revisiting the Power of Prompt for Visual Tuning

Yuzhu Wang, Lechao Cheng, Chaowei Fang, Dingwen Zhang, Manni Duan

Executable Code Actions Elicit Better LLM Agents

Xingyao Wang, Yangyi Chen, Lifan Yuan, Yizhe Zhang, Yunzhu Li

A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design

Zhihai Wang, Lei Chen, Jie Wang, Yinqi Bai, Xing Li

Non-parametric Online Change Point Detection on Riemannian Manifolds

Xiuheng Wang, Ricardo Augusto Borsoi, Cédric Richard

Towards Theoretical Understanding of Learning Large-scale Dependent Data via Random Features

Chao Wang, Xin Bing, XIN HE, Caixing Wang

Adversarially Robust Hypothesis Transfer Learning

Yunjuan Wang, Raman Arora

On Universally Optimal Algorithms for A/B Testing

Po-An Wang, Kaito Ariu, Alexandre Proutiere

One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts

Ruochen Wang, Sohyun An, Minhao Cheng, Tianyi Zhou, Sung Ju Hwang

Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation

Xinyi Wang, Alfonso Amayuelas, Kexun Zhang, Liangming Pan, Wenhu Chen

Towards Unified Multi-granularity Text Detection with Interactive Attention

Xingyu Wan, Chengquan Zhang, Pengyuan Lyu, Sen Fan, Zihan Ni

Non-stationary Online Convex Optimization with Arbitrary Delays

Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang

S3GCL: Spectral, Swift, Spatial Graph Contrastive Learning

Guancheng Wan, Yijun Tian, Wenke Huang, Nitesh V Chawla, Mang Ye

Superpoint Gaussian Splatting for Real-Time High-Fidelity Dynamic Scene Reconstruction

Diwen Wan, Ruijie Lu, Gang Zeng

Decouple then Classify: A Dynamic Multi-view Labeling Strategy with Shared and Specific Information

Xinhang Wan, Jiyuan Liu, Xinwang Liu, Yi Wen, Hao Yu

VinT-6D: A Large-Scale Object-in-hand Dataset from Vision, Touch and Proprioception

Zhaoliang Wan, Yonggen Ling, Senlin Yi, Lu Qi, Wang Wei Lee

AlphaZero-Like Tree-Search can Guide Large Language Model Decoding and Training

Ziyu Wan, Xidong Feng, Muning Wen, Stephen Marcus McAleer, Ying Wen

SeMOPO: Learning High-quality Model and Policy from Low-quality Offline Visual Datasets

Shenghua Wan, Ziyuan Chen, Le Gan, Shuai Feng, De-Chuan Zhan

Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD

Yijun Wan, Melih Barsbey, Abdellatif Zaidi, Umut Simsekli

Log Neural Controlled Differential Equations: The Lie Brackets Make A Difference

Benjamin Walker, Andrew Donald Mcleod, Tiexin Qin, Yichuan Cheng, Haoliang Li

Trustless Audits without Revealing Data or Models

Suppakit Waiwitlikhit, Ion Stoica, Yi Sun, Tatsunori Hashimoto, Daniel Kang

Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations

Stefan Sylvius Wagner, Stefan Harmeling

ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models

Rohan Wadhawan, Hritik Bansal, Kai-Wei Chang, Nanyun Peng

Deconstructing the Goldilocks Zone of Neural Network Initialization

Artem M Vysogorets, Anna Dawid, Julia Kempe

Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning

Nikhil Vyas, Depen Morwani, Rosie Zhao, Gal Kaplun, Sham M. Kakade

Convergence of Some Convex Message Passing Algorithms to a Fixed Point

Václav Voráček, Tomas Werner

A Language Model’s Guide Through Latent Space

Dimitri von Rütte, Sotiris Anagnostidis, Gregor Bachmann, Thomas Hofmann

ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations

Kailas Vodrahalli, James Zou

Optimal Transport for Structure Learning Under Missing Data

Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Phung

Parameter Estimation in DAGs from Incomplete Data via Optimal Transport

Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla

CF-OPT: Counterfactual Explanations for Structured Prediction

Germain Vivier-Ardisson, Alexandre Forel, Axel Parmentier, Thibaut Vidal

ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy

Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu

Position: Will we run out of data? Limits of LLM scaling based on human-generated data

Pablo Villalobos, Anson Ho, Jaime Sevilla, Tamay Besiroglu, Lennart Heim

Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience

Martina G. Vilas, Federico Adolfi, David Poeppel, Gemma Roig

Imitation Learning in Discounted Linear MDPs without exploration assumptions

Luca Viano, Stratis Skoulakis, Volkan Cevher

To the Max: Reinventing Reward in Reinforcement Learning

Grigorii Veviurko, Wendelin Boehmer, Mathijs de Weerdt

On a Neural Implementation of Brenier’s Polar Factorization

Nina Vesseron, Marco Cuturi

CuTS: Customizable Tabular Synthetic Data Generation

Mark Vero, Mislav Balunovic, Martin Vechev

Topological Neural Networks go Persistent, Equivariant, and Continuous

Yogesh Verma, Amauri H Souza, Vikas Garg

Code as Reward: Empowering Reinforcement Learning with VLMs

David Venuto, Mohammad Sami Nur Islam, Martin Klissarov, Doina Precup, Sherry Yang

Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models

Raviteja Vemulapalli, Hadi Pouransari, Fartash Faghri, Sachin Mehta, Mehrdad Farajtabar

Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features

Rodrigo Veiga, Anastasia Remizova, Nicolas Macris

A Probabilistic Approach to Learning the Degree of Equivariance in Steerable CNNs

Lars Veefkind, Gabriele Cesa

Optimization without Retraction on the Random Generalized Stiefel Manifold

Simon Vary, Pierre Ablin, Bin Gao, Pierre-antoine Absil

Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution

Elen Vardanyan, Sona Hunanyan, Tigran Galstyan, Arshak Minasyan, Arnak S. Dalalyan

Discovering Mixtures of Structural Causal Models from Time Series Data

Sumanth Varambally, Yian Ma, Rose Yu