ICML 2024

2,610 papers

Minimizing f-Divergences by Interpolating Velocity Fields

Song Liu, Jiahao Yu, Jack Simons, Mingxuan Yi, Mark Beaumont

In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering

Sheng Liu, Haotian Ye, Lei Xing, James Y. Zou

Building Socially-Equitable Public Models

Yejia Liu, Jianyi Yang, Pengfei Li, Tongxin Li, Shaolei Ren

Partial Multi-View Multi-Label Classification via Semantic Invariance Learning and Prototype Modeling

Chengliang Liu, Gehui Xu, Jie Wen, Yabo Liu, Chao Huang

Causality Based Front-door Defense Against Backdoor Attack on Language Models

Yiran Liu, Xiaoang Xu, Zhiyi Hou, Yang Yu

Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning

Biao Liu, Ning Xu, Xiangyu Fang, Xin Geng

Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model

Fei Liu, Tong Xialiang, Mingxuan Yuan, Xi Lin, Fu Luo

Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications

Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Bo Li

Language-Driven Cross-Modal Classifier for Zero-Shot Multi-Label Image Recognition

Yicheng Liu, Jie Wen, Chengliang Liu, Xiaozhao Fang, Zuoyong Li

Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond

Xutong Liu, Siwei Wang, Jinhang Zuo, Han Zhong, Xuchuang Wang

High-Probability Bound for Non-Smooth Non-Convex Stochastic Optimization with Heavy Tails

Langqi Liu, Yibo Wang, Lijun Zhang

DoRA: Weight-Decomposed Low-Rank Adaptation

Shih-Yang Liu, Chien-Yi Wang, Hongxu Yin, Pavlo Molchanov, Yu-Chiang Frank Wang

LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models

Tianci Liu, Haoyu Wang, Shiyang Wang, Yu Cheng, Jing Gao

TimeX++: Learning Time-Series Explanations with Information Bottleneck

Zichuan Liu, Tianchun Wang, Jimeng Shi, Xu Zheng, Zhuomin Chen

DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation

Qinshuo Liu, Zixin Wang, Xi’An Li, Xinyao Ji, Lei Zhang

Symmetric Matrix Completion with ReLU Sampling

Huikang Liu, Peng Wang, Longxiu Huang, Qing Qu, Laura Balzano

Differentiable Model Scaling using Differentiable Topk

Kai Liu, Ruohui Wang, Jianfei Gao, Kai Chen

Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding

Guangyi Liu, Yu Wang, Zeyu Feng, Qiyu Wu, Liping Tang

Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement

Che Liu, Zhongwei Wan, Cheng Ouyang, Anand Shah, Wenjia Bai

New Sample Complexity Bounds for Sample Average Approximation in Heavy-Tailed Stochastic Programming

Hongcheng Liu, Jindong Tong

Entropy-Reinforced Planning with Large Language Models for Drug Discovery

Xuefeng Liu, Chih-chan Tien, Peng Ding, Songhao Jiang, Rick L. Stevens

Perfect Alignment May be Poisonous to Graph Contrastive Learning

Jingyu Liu, Huayi Tang, Yong Liu

Causal Discovery via Conditional Independence Testing with Proxy Variables

Mingzhou Liu, Xinwei Sun, Yu Qiao, Yizhou Wang

How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?

Ryan Liu, Theodore Sumers, Ishita Dasgupta, Thomas L. Griffiths

Federated Representation Learning in the Under-Parameterized Regime

Renpu Liu, Cong Shen, Jing Yang

Generative Marginalization Models

Sulin Liu, Peter Ramadge, Ryan P Adams

Class-Imbalanced Graph Learning without Class Rebalancing

Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Hyunsik Yoo, David Zhou

Fast Decision Boundary based Out-of-Distribution Detector

Litian Liu, Yao Qin

Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization

Yirui Liu, Xinghao Qiao, Yulong Pei, Liying Wang

Floating Anchor Diffusion Model for Multi-motif Scaffolding

Ke Liu, Weian Mao, Shuaike Shen, Xiaoran Jiao, Zheng Sun

KnowFormer: Revisiting Transformers for Knowledge Graph Reasoning

Junnan Liu, Qianren Mao, Weifeng Jiang, Jianxin Li

Amortized Equation Discovery in Hybrid Dynamical Systems

Yongtuo Liu, Sara Magliacane, Miltiadis Kofinas, Stratis Gavves

Revisiting Context Aggregation for Image Matting

Qinglin Liu, Xiaoqian Lv, Quanling Meng, Zonglin Li, Xiangyuan Lan

Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency

Yangfan Liu, Jiaqi Lv, Xin Geng, Ning Xu

Position: Foundation Agents as the Paradigm Shift for Decision Making

Xiaoqian Liu, Xingzhou Lou, Jianbin Jiao, Junge Zhang

Moreau Envelope for Nonconvex Bi-Level Optimization: A Single-Loop and Hessian-Free Solution Strategy

Risheng Liu, Zhu Liu, Wei Yao, Shangzhi Zeng, Jin Zhang

Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning

Xu-Hui Liu, Tian-Shuo Liu, Shengyi Jiang, Ruifeng Chen, Zhilong Zhang

Convergence of Online Learning Algorithm for a Mixture of Multiple Linear Regressions

Yujing Liu, Zhixin Liu, Lei Guo

Characterizing ResNet’s Universal Approximation Capability

Chenghao Liu, Enming Liang, Minghua Chen

Differentiable Combinatorial Scheduling at Scale

Mingju Liu, Yingjie Li, Jiaqi Yin, Zhiru Zhang, Cunxi Yu

Short-Long Convolutions Help Hardware-Efficient Linear Attention to Focus on Long Sequences

Zicheng Liu, Siyuan Li, Li Wang, Zedong Wang, Yunfan Liu

Two-timescale Derivative Free Optimization for Performative Prediction with Markovian Data

Haitong Liu, Qiang Li, Hoi To Wai

Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning

Tenglong Liu, Yang Li, Yixing Lan, Hao Gao, Wei Pan

From Generalization Analysis to Optimization Designs for State Space Models

Fusheng Liu, Qianxiao Li

Multi-Source Conformal Inference Under Distribution Shift

Yi Liu, Alexander Levis, Sharon-Lise Normand, Larry Han

Stereo Risk: A Continuous Modeling Approach to Stereo Matching

Ce Liu, Suryansh Kumar, Shuhang Gu, Radu Timofte, Yao Yao

Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning

Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang

StyDeSty: Min-Max Stylization and Destylization for Single Domain Generalization

Songhua Liu, Xin Jin, Xingyi Yang, Jingwen Ye, Xinchao Wang

Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation

Pei Liu, Luping Ji

Reason for Future, Act for Now: A Principled Architecture for Autonomous LLM Agents

Zhihan Liu, Hao Hu, Shenao Zhang, Hongyi Guo, Shuqi Ke

Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion

Xuantong Liu, Tianyang Hu, Wenjia Wang, Kenji Kawaguchi, Yuan Yao

Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy

Yi Liu, Qirui Hu, Linglong Kong

Online Speculative Decoding

Xiaoxuan Liu, Lanxiang Hu, Peter Bailis, Alvin Cheung, Zhijie Deng

On the Feasibility of Single-Pass Full-Capacity Learning in Linear Threshold Neurons with Binary Input Vectors

Ruipeng Liu, Borui He, Naveed Tahir, Garrett Ethan Katz

ELTA: An Enhancer against Long-Tail for Aesthetics-oriented Models

Limin Liu, Shuai He, Anlong Ming, Rui Xie, Huadong Ma

PAPM: A Physics-aware Proxy Model for Process Systems

Pengwei Liu, Zhongkai Hao, Xingyu Ren, Hangjie Yuan, Jiayang Ren

Unlock the Cognitive Generalization of Deep Reinforcement Learning via Granular Ball Representation

Jiashun Liu, Jianye Hao, Yi Ma, Shuyin Xia

Bidirectional Reciprocative Information Communication for Few-Shot Semantic Segmentation

YUANWEI LIU, Junwei Han, Xiwen Yao, Salman Khan, Hisham Cholakkal

DIDI: Diffusion-Guided Diversity for Offline Behavioral Generation

Jinxin Liu, Xinghong Guo, Zifeng Zhuang, Donglin Wang

Decoding-time Realignment of Language Models

Tianlin Liu, Shangmin Guo, Leonardo Bianco, Daniele Calandriello, Quentin Berthet

Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss

Zhenlong Liu, Lei Feng, HUIPING ZHUANG, Xiaofeng Cao, Hongxin Wei

Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws

Ning Liu, Yiming Fan, Xianyi Zeng, Milan Klöwer, Lu Zhang

PEARL: Zero-shot Cross-task Preference Alignment and Robust Reward Learning for Robotic Manipulation

Runze Liu, Yali Du, Fengshuo Bai, Jiafei Lyu, Xiu Li

Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models

Songtao Liu, Hanjun Dai, Yue Zhao, Peng Liu

The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks

Ziquan Liu, Yufei CUI, Yan Yan, Yi Xu, Xiangyang Ji

ESNet: Evolution and Succession Network for High-Resolution Salient Object Detection

Hongyu Liu, Runmin Cong, Hua Li, Qianqian Xu, Qingming Huang

Unifying Image Processing as Visual Prompting Question Answering

Yihao Liu, Xiangyu Chen, Xianzheng Ma, Xintao Wang, Jiantao Zhou

Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization

Zhuanghua Liu, Cheng Chen, Luo Luo, Bryan Kian Hsiang Low

Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers

Yuxing Liu, Lesi Chen, Luo Luo

Graph Adversarial Diffusion Convolution

Songtao Liu, Jinghui Chen, Tianfan Fu, Lu Lin, Marinka Zitnik

ReLU Network with Width d+O(1) Can Achieve Optimal Approximation Rate

Chenghao Liu, Minghua Chen

Enhancing Adversarial Robustness in SNNs with Sparse Gradients

Yujia Liu, Tong Bu, Jianhao Ding, Zecheng Hao, Tiejun Huang

Adaptive Text Watermark for Large Language Models

Yepeng Liu, Yuheng Bu

Graph Distillation with Eigenbasis Matching

Yang Liu, Deyu Bo, Chuan Shi

Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty

Kaizhao Liu, Jose Blanchet, Lexing Ying, Yiping Lu

Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals

Ziyi Liu, Idan Attias, Daniel M. Roy

Scaling Tractable Probabilistic Circuits: A Systems Perspective

Anji Liu, Kareem Ahmed, Guy Van den Broeck

Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains

Levi E. Lingsch, Mike Yan Michelis, Emmanuel de Bézenac, Sirani M. Perera, Robert K. Katzschmann

Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures

Zenan Ling, Longbo Li, Zhanbo Feng, YIXUAN ZHANG, Feng Zhou

Position: A Call to Action for a Human-Centered AutoML Paradigm

Marius Lindauer, Florian Karl, Anne Klier, Julia Moosbauer, Alexander Tornede

Plug-in Performative Optimization

Licong Lin, Tijana Zrnic

Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras

Tzu-Yuan Lin, Minghan Zhu, Maani Ghaffari

PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching

Haitao Lin, Odin Zhang, Huifeng Zhao, Dejun Jiang, Lirong Wu

Smooth Tchebycheff Scalarization for Multi-Objective Optimization

Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Fei Liu, Zhenkun Wang

Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification

Xixun Lin, Wenxiao Zhang, Fengzhao Shi, Chuan Zhou, Lixin Zou

Autonomous Sparse Mean-CVaR Portfolio Optimization

Yizun Lin, Yangyu Zhang, Zhao-Rong Lai, Cheng Li

Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency

Runqi Lin, Chaojian Yu, Bo Han, Hang Su, Tongliang Liu

A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes

Zhenwei Lin, Chenyu Xue, Qi Deng, Yinyu Ye

Distributionally Robust Data Valuation

Xiaoqiang Lin, Xinyi Xu, Zhaoxuan Wu, See-Kiong Ng, Bryan Kian Hsiang Low

GeoAB: Towards Realistic Antibody Design and Reliable Affinity Maturation

Haitao Lin, Lirong Wu, Yufei Huang, Yunfan Liu, Odin Zhang

Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers

Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai, Wenyang Hu, YAO SHU

Smoothness Adaptive Hypothesis Transfer Learning

Haotian Lin, Matthew Reimherr

On Hypothesis Transfer Learning of Functional Linear Models

Haotian Lin, Matthew Reimherr

Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits

Jiabin Lin, Shana Moothedath, Namrata Vaswani

SparseTSF: Modeling Long-term Time Series Forecasting with *1k* Parameters

Shengsheng Lin, Weiwei Lin, Wentai Wu, Haojun Chen, Junjie Yang

HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network

Bor-Jiun Lin, Chun-Yi Lee

Dual Operating Modes of In-Context Learning

Ziqian Lin, Kangwook Lee

Graph-enhanced Large Language Models in Asynchronous Plan Reasoning

Fangru Lin, Emanuele La Malfa, Valentin Hofmann, Elle Michelle Yang, Anthony G. Cohn

Selecting Large Language Model to Fine-tune via Rectified Scaling Law

Haowei Lin, Baizhou Huang, Haotian Ye, Qinyu Chen, Zihao Wang

Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency

Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji