ICML 2024

2,610 papers

Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data

Kang Lin, Reinhard Heckel

Learning to Model the World With Language

Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner, Pieter Abbeel

Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC

Wu Lin, Felix Dangel, Runa Eschenhagen, Kirill Neklyudov, Agustinus Kristiadi

Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective

Wu Lin, Felix Dangel, Runa Eschenhagen, Juhan Bae, Richard E. Turner

Non-confusing Generation of Customized Concepts in Diffusion Models

Wang Lin, Jingyuan Chen, Jiaxin Shi, Yichen Zhu, Chen Liang

Revisiting the Role of Language Priors in Vision-Language Models

Zhiqiu Lin, Xinyue Chen, Deepak Pathak, Pengchuan Zhang, Deva Ramanan

Equivariant Diffusion for Crystal Structure Prediction

Peijia Lin, Pin Chen, Rui Jiao, Qing Mo, Cen Jianhuan

An Effective Dynamic Gradient Calibration Method for Continual Learning

Weichen Lin, Jiaxiang Chen, Ruomin Huang, Hu Ding

Momentum Particle Maximum Likelihood

Jen Ning Lim, Juan Kuntz, Samuel Power, Adam Michael Johansen

Graph Geometry-Preserving Autoencoders

Jungbin Lim, Jihwan Kim, Yonghyeon LEE, Cheongjae Jang, Frank C. Park

Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning

Yun-Hsuan Lien, Ping-Chun Hsieh, Tzu-Mao Li, Yu-Shuen Wang

Bootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium

Luofeng Liao, Christian Kroer

On the Error-Propagation of Inexact Hotelling’s Deflation for Principal Component Analysis

Fangshuo Liao, Junhyung Lyle Kim, Cruz Barnum, Anastasios Kyrillidis

Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation

Weixuan Liang, En Zhu, Shengju Yu, Huiying Xu, Xinzhong Zhu

Efficient Precision and Recall Metrics for Assessing Generative Models using Hubness-aware Sampling

Yuanbang Liang, Jing Wu, Yu-Kun Lai, Yipeng Qin

Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization

Jian Liang, Lijun Sheng, Zhengbo Wang, Ran He, Tieniu Tan

Single-Trajectory Distributionally Robust Reinforcement Learning

Zhipeng Liang, Xiaoteng Ma, Jose Blanchet, Jun Yang, Jiheng Zhang

Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs

Langzhang Liang, Sunwoo Kim, Kijung Shin, Zenglin Xu, Shirui Pan

Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews

Weixin Liang, Zachary Izzo, Yaohui Zhang, Haley Lepp, Hancheng Cao

Graph External Attention Enhanced Transformer

Jianqing Liang, Min Chen, Jiye Liang

Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset

Shijie Lian, Ziyi Zhang, Hua Li, Wenjie Li, Laurence Tianruo Yang

Receptive Fields As Experts in Convolutional Neural Architectures

Dongze Lian, Weihao Yu, Xinchao Wang

Kepler codebook

Junrong Lian, Ziyue Dong, Pengxu Wei, Wei Ke, Chang Liu

Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses

Shaojie Li, Bowei Zhu, Yong Liu

DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning

Jianxiong Li, Jinliang Zheng, Yinan Zheng, Liyuan Mao, Xiao Hu

Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering

Haoxuan Li, Chunyuan Zheng, Shuyi Wang, Kunhan Wu, Eric Wang

EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search

Pengyi Li, YAN ZHENG, Hongyao Tang, Xian Fu, Jianye Hao

Feel-Good Thompson Sampling for Contextual Dueling Bandits

Xuheng Li, Heyang Zhao, Quanquan Gu

From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems

Xin Li, Jingdong Zhang, Qunxi Zhu, Chengli Zhao, Xue Zhang

Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks

Haoyu Li, Shichang Zhang, Longwen Tang, Mathieu Bauchy, Yizhou Sun

Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error

Haoran Li, Zicheng Zhang, Wang Luo, Congying Han, Yudong Hu

Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms

Yichen Li, Chicheng Zhang

Seesaw: Compensating for Nonlinear Reduction with Linear Computations for Private Inference

Fabing Li, Yuanhao Zhai, Shuangyu Cai, Mingyu Gao

Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis

Yingying Li, Jing Yu, Lauren Conger, Taylan Kargin, Adam Wierman

GeoReasoner: Geo-localization with Reasoning in Street Views using a Large Vision-Language Model

Ling Li, Yu Ye, Bingchuan Jiang, Wei Zeng

KernelWarehouse: Rethinking the Design of Dynamic Convolution

CHAO LI, Anbang Yao

IIANet: An Intra- and Inter-Modality Attention Network for Audio-Visual Speech Separation

Kai Li, Runxuan Yang, Fuchun Sun, Xiaolin Hu

PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming

Bingheng Li, Linxin Yang, Yupeng Chen, Senmiao Wang, Haitao Mao

ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Ziniu Li, Tian Xu, Yushun Zhang, ZhiHang Lin, Yang Yu

Statistical Properties of Robust Satisficing

Zhiyi Li, Yunbei Xu, Ruohan Zhan

Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process

Zichong Li, Qunzhi Xu, Zhenghao Xu, Yajun Mei, Tuo Zhao

FedBAT: Communication-Efficient Federated Learning via Learnable Binarization

Shiwei Li, Wenchao Xu, Haozhao Wang, Xing Tang, Yining Qi

Towards efficient deep spiking neural networks construction with spiking activity based pruning

Yaxin Li, Qi Xu, Jiangrong Shen, Hongming Xu, Long Chen

Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent

Yingru Li, Jiawei Xu, Lei Han, Zhi-Quan Luo

Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection

Feiran Li, Qianqian Xu, Shilong Bao, Zhiyong Yang, Runmin Cong

FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction

Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang

Towards Realistic Model Selection for Semi-supervised Learning

Muyang Li, Xiaobo Xia, Runze Wu, Fengming Huang, Jun Yu

Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias

Baohong Li, Anpeng Wu, Ruoxuan Xiong, Kun Kuang

EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty

Yuhui Li, Fangyun Wei, Chao Zhang, Hongyang Zhang

The Good, The Bad, and Why: Unveiling Emotions in Generative AI

Cheng Li, Jindong Wang, YIXUAN ZHANG, Kaijie Zhu, Xinyi Wang

Disentangled Graph Self-supervised Learning for Out-of-Distribution Generalization

Haoyang Li, Xin Wang, Zeyang Zhang, Haibo Chen, Ziwei Zhang

Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy

Bo Li, Wei Wang, Peng Ye

OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift

Lin Li, Yifei Wang, Chawin Sitawarin, Michael W. Spratling

What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding

Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, ZAIXI ZHANG

How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?

Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen

VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling

Siyuan Li, Zedong Wang, Zicheng Liu, Di Wu, Cheng Tan

Compress Clean Signal from Noisy Raw Image: A Self-Supervised Approach

Zhihao Li, Yufei Wang, Alex Kot, Bihan Wen

Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning

Depeng Li, Tianqi Wang, Junwei Chen, Wei Dai, Zhigang Zeng

DiffFPR: Diffusion Prior for Oversampled Fourier Phase Retrieval

Ji Li, Chao Wang

LoRAP: Transformer Sub-Layers Deserve Differentiated Structured Compression for Large Language Models

Guangyan Li, Yongqiang Tang, Wensheng Zhang

Combining Experimental and Historical Data for Policy Evaluation

ting li, Chengchun Shi, Qianglin Wen, Yang Sui, Yongli Qin

Privacy Preserving Adaptive Experiment Design

Jiachun Li, Kaining Shi, David Simchi-Levi

DiffStitch: Boosting Offline Reinforcement Learning with Diffusion-based Trajectory Stitching

Guanghe Li, Yixiang Shan, Zhengbang Zhu, Ting Long, Weinan Zhang

When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions

Zhening Li, Gabriel Poesia, Armando Solar-Lezama

Graph Neural Network Explanations are Fragile

Jiate Li, Meng Pang, Yun Dong, Jinyuan Jia, Binghui Wang

The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning

Nathaniel Li, Alexander Pan, Anjali Gopal, Summer Yue, Daniel Berrios

Evaluating Quantized Large Language Models

Shiyao Li, Xuefei Ning, Luning Wang, Tengxuan Liu, Xiangsheng Shi

Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining

Aaron Jiaxun Li, Robin Netzorg, Zhihan Cheng, Zhuoqin Zhang, Bin Yu

A Contextual Combinatorial Bandit Approach to Negotiation

Yexin Li, Zhancun Mu, Siyuan Qi

PID: Prompt-Independent Data Protection Against Latent Diffusion Models

Ang Li, Yichuan Mo, Mingjie Li, Yisen Wang

Learning Adaptive and View-Invariant Vision Transformer for Real-Time UAV Tracking

Yongxin Li, Mengyuan Liu, You Wu, Xucheng Wang, Xiangyang Yang

Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning

Xinran Li, Zifan Liu, Shibo Chen, Jun Zhang

Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once

Zhangheng Li, Shiwei Liu, Tianlong Chen, Ajay Kumar Jaiswal, Zhenyu Zhang

Concentration Inequalities for General Functions of Heavy-Tailed Random Variables

Shaojie Li, Yong Liu

A Theoretical Analysis of Backdoor Poisoning Attacks in Convolutional Neural Networks

Boqi Li, Weiwei Liu

Preventing Model Collapse in Gaussian Process Latent Variable Models

Ying Li, Zhidi Lin, Feng Yin, Michael Minyi Zhang

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator

Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman

Cascade-CLIP: Cascaded Vision-Language Embeddings Alignment for Zero-Shot Semantic Segmentation

Yunheng Li, Zhong-Yu Li, Quan-Sheng Zeng, Qibin Hou, Ming-Ming Cheng

A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data

Wenqiang Li, Weijun Li, Lina Yu, Min Wu, Linjun Sun

Enhancing Class-Imbalanced Learning with Pre-Trained Guidance through Class-Conditional Knowledge Distillation

Lan Li, Xin-Chun Li, Han-Jia Ye, De-Chuan Zhan

Configurable Mirror Descent: Towards a Unification of Decision Making

Pengdeng Li, Shuxin Li, Chang Yang, Xinrun Wang, Shuyue Hu

Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias

Baohong Li, Haoxuan Li, Ruoxuan Xiong, Anpeng Wu, Fei Wu

A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective

Baohong Li, Haoxuan Li, Anpeng Wu, Minqin Zhu, Shiyuan Peng

Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions

Weihan Li, Chengrui Li, Yule Wang, Anqi Wu

A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing

Chengrui Li, Weihan Li, Yule Wang, Anqi Wu

Neural Collapse in Multi-label Learning with Pick-all-label Loss

Pengyu Li, Xiao Li, Yutong Wang, Qing Qu

Generalizing Knowledge Graph Embedding with Universal Orthogonal Parameterization

Rui Li, Chaozhuo Li, Yanming Shen, Zeyu Zhang, Xu Chen

Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models

Jinhao Li, Haopeng Li, Sarah Monazam Erfani, Lei Feng, James Bailey

Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines

Yuchen Li, Alexandre Kirchmeyer, Aashay Mehta, Yilong Qin, Boris Dadachev

Q-Probe: A Lightweight Approach to Reward Maximization for Language Models

Kenneth Li, Samy Jelassi, Hugh Zhang, Sham M. Kakade, Martin Wattenberg

Accelerating Convergence of Score-Based Diffusion Models, Provably

Gen Li, Yu Huang, Timofey Efimov, Yuting Wei, Yuejie Chi

Integrating Global Context Contrast and Local Sensitivity for Blind Image Quality Assessment

Xudong Li, Runze Hu, Jingyuan Zheng, Yan Zhang, ShengChuan Zhang

VisionGraph: Leveraging Large Multimodal Models for Graph Theory Problems in Visual Context

Yunxin Li, Baotian Hu, Haoyuan Shi, Wei Wang, Longyue Wang

Image Clustering with External Guidance

Yunfan Li, Peng Hu, Dezhong Peng, Jiancheng Lv, Jianping Fan

Value-Evolutionary-Based Reinforcement Learning

Pengyi Li, Jianye Hao, Hongyao Tang, YAN ZHENG, Fazl Barez

Graph Structure Extrapolation for Out-of-Distribution Generalization

Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji

Mastering Robot Manipulation with Multimodal Prompts through Pretraining and Multi-task Fine-tuning

Jiachen Li, Qiaozi Gao, Michael Johnston, Xiaofeng Gao, Xuehai He

Adaptive Feature Selection for No-Reference Image Quality Assessment by Mitigating Semantic Noise Sensitivity

Xudong Li, Timin Gao, Runze Hu, Yan Zhang, ShengChuan Zhang

Automated Statistical Model Discovery with Language Models

Michael Y. Li, Emily Fox, Noah Goodman

Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection

Yuxin Li, Yaoxuan Feng, Bo Chen, wenchao chen, Yubiao Wang