ICML 2024

2,610 papers

RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning

Boning Li, Zhixuan Fang, Longbo Huang

Improving Context Understanding in Multimodal Large Language Models via Multimodal Composition Learning

Wei Li, Hehe Fan, Yongkang Wong, Yi Yang, Mohan Kankanhalli

Debiased Distribution Compression

Lingxiao Li, Raaz Dwivedi, Lester Mackey

FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning

Wenzhe Li, Zihan Ding, Seth Karten, Chi Jin

Positive and Unlabeled Learning with Controlled Probability Boundary Fence

Changchun Li, Yuanchao Dai, Lei Feng, Ximing Li, Bing Wang

Full-Atom Peptide Design based on Multi-modal Flow Matching

Jiahan Li, Chaoran Cheng, Zuofan Wu, Ruihan Guo, Shitong Luo

Two-sided Competing Matching Recommendation Markets With Quota and Complementary Preferences Constraints

Yuantong Li, Guang Cheng, Xiaowu Dai

ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking

Wenshuo Li, Xinghao Chen, Han Shu, Yehui Tang, Yunhe Wang

Data Poisoning Attacks against Conformal Prediction

Yangyi Li, Aobo Chen, Wei Qian, Chenxu Zhao, Divya Lidder

Evolving Subnetwork Training for Large Language Models

Hanqi Li, Lu Chen, Da Ma, Zijian Wu, Su Zhu

Completing Visual Objects via Bridging Generation and Segmentation

Xiang Li, Yinpeng Chen, Chung-Ching Lin, Hao Chen, Kai Hu

GiLOT: Interpreting Generative Language Models via Optimal Transport

Xuhong Li, Jiamin Chen, Yekun Chai, Haoyi Xiong

Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition

Yuke Li, Guangyi Chen, Ben Abramowitz, Stefano Anzellotti, Donglai Wei

Critical windows: non-asymptotic theory for feature emergence in diffusion models

Marvin Li, Sitan Chen

Improving Neural Logic Machines via Failure Reflection

Zhiming Li, Yushi Cao, YAN ZHENG, Xu Liu, Bozhi Wu

Purifying Quantization-conditioned Backdoors via Layer-wise Activation Correction with Distribution Approximation

Boheng Li, Yishuo Cai, Jisong Cai, Yiming Li, Han Qiu

Denoising Autoregressive Representation Learning

Yazhe Li, Jörg Bornschein, Ting Chen

DetKDS: Knowledge Distillation Search for Object Detectors

Lujun Li, Yufan Bao, Peijie Dong, Chuanguang Yang, Anggeng Li

Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms

Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu

Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models

Francesca-Zhoufan Li, Ava P Amini, Yisong Yue, Kevin K Yang, Alex Xijie Lu

Eluder-based Regret for Stochastic Contextual MDPs

Orin Levy, Asaf Cassel, Alon Cohen, Yishay Mansour

Cell2Sentence: Teaching Large Language Models the Language of Biology

Daniel Levine, Syed A Rizvi, Sacha Levy, Nazreen Pallikkavaliyaveetil, David Zhang

Online Isolation Forest

Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer, Albert Bifet, Giacomo Boracchi

Winner-takes-all learners are geometry-aware conditional density estimators

Victor Letzelter, David Perera, Cédric ROMMEL, Mathieu Fontaine, Slim Essid

Improving Gradient-Guided Nested Sampling for Posterior Inference

Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh

An Independence-promoting Loss for Music Generation with Language Models

Jean-Marie Lemercier, Simon Rouard, Jade Copet, Yossi Adi, Alexandre Defossez

Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates

Rémi Leluc, Aymeric Dieuleveut, François Portier, Johan Segers, Aigerim Zhuman

Langevin Policy for Safe Reinforcement Learning

Fenghao Lei, Long Yang, Shiting Wen, Zhixiong Huang, Zhiwang Zhang

A Geometric Decomposition of Finite Games: Convergence vs. Recurrence under Exponential Weights

Davide Legacci, Panayotis Mertikopoulos, Bary Pradelski

Sign Rank Limitations for Inner Product Graph Decoders

Su Hyeong Lee, Qingqi Zhang, Risi Kondor

STELLA: Continual Audio-Video Pre-training with SpatioTemporal Localized Alignment

Jaewoo Lee, Jaehong Yoon, Wonjae Kim, Yunji Kim, Sung Ju Hwang

BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation

Daeun Lee, Jaehong Yoon, Sung Ju Hwang

Rethinking the Flat Minima Searching in Federated Learning

Taehwan Lee, Sung Whan Yoon

Improving Instruction Following in Language Models through Proxy-Based Uncertainty Estimation

JoonHo Lee, Jae Oh Woo, Juree Seok, Parisa Hassanzadeh, Wooseok Jang

Behavior Generation with Latent Actions

Seungjae Lee, Yibin Wang, Haritheja Etukuru, H. Jin Kim, Nur Muhammad Mahi Shafiullah

Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space

Minji Lee, Luiz Felipe Vecchietti, Hyunkyu Jung, Hyun Joo Ro, Meeyoung Cha

Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization

Deokjae Lee, Hyun Oh Song, Kyunghyun Cho

Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains

Kyungeun Lee, Ye Seul Sim, Hyeseung Cho, Moonjung Eo, Suhee Yoon

StrWAEs to Invariant Representations

Hyunjong Lee, Yedarm Seong, Sungdong Lee, Joong-Ho Won

RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Harrison Lee, Samrat Phatale, Hassan Mansoor, Thomas Mesnard, Johan Ferret

3D Geometric Shape Assembly via Efficient Point Cloud Matching

Nahyuk Lee, Juhong Min, Junha Lee, Seungwook Kim, Kanghee Lee

Why Do Animals Need Shaping? A Theory of Task Composition and Curriculum Learning

Jin Hwa Lee, Stefano Sarao Mannelli, Andrew M Saxe

Defining Neural Network Architecture through Polytope Structures of Datasets

Sangmin Lee, Abbas Mammadov, Jong Chul Ye

Supervised Matrix Factorization: Local Landscape Analysis and Applications

Joowon Lee, Hanbaek Lyu, Weixin Yao

Drug Discovery with Dynamic Goal-aware Fragments

Seul Lee, Seanie Lee, Kenji Kawaguchi, Sung Ju Hwang

Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity

Hagyeong Lee, Minkyu Kim, Jun-Hyuk Kim, Seungeon Kim, Dokwan Oh

Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective

Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang

Pausing Policy Learning in Non-stationary Reinforcement Learning

Hyunin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi

Graph Neural Networks with a Distribution of Parametrized Graphs

See Hian Lee, Feng Ji, Kelin Xia, Wee Peng Tay

Learning to Continually Learn with the Bayesian Principle

Soochan Lee, Hyeonseong Jeon, Jaehyeon Son, Gunhee Kim

PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning

Jaejun Lee, Minsung Hwang, Joyce Jiyoung Whang

Recurrent Early Exits for Federated Learning with Heterogeneous Clients

Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis

SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching

Yongmin Lee, Hye Won Chung

DataFreeShield: Defending Adversarial Attacks without Training Data

Hyeyoon Lee, Kanghyun Choi, Dain Kwon, SunJong Park, Mayoore Selvarasa Jaiswal

Fundamental Benefit of Alternating Updates in Minimax Optimization

Jaewook Lee, Hanseul Cho, Chulhee Yun

Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Hojoon Lee, Hyeonseo Cho, HYUNSEUNG KIM, Donghu Kim, Dugki Min

A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Kuang-Huei Lee, Xinyun Chen, Hiroki Furuta, John Canny, Ian Fischer

Stationary Latent Weight Inference for Unreliable Observations from Online Test-Time Adaptation

Jae-Hong Lee, Joon-Hyuk Chang

A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity

Andrew Lee, Xiaoyan Bai, Itamar Pres, Martin Wattenberg, Jonathan K. Kummerfeld

Generalization Analysis of Deep Non-linear Matrix Completion

Antoine Ledent, Rodrigo Alves

Chasing Convex Functions with Long-term Constraints

Adam Lechowicz, Nicolas Christianson, Bo Sun, Noman Bashir, Mohammad Hajiesmaili

Run-Time Task Composition with Safety Semantics

Kevin Leahy, Makai Mann, Zachary Serlin

Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm

Batiste Le Bars, Aurélien Bellet, Marc Tommasi, Kevin Scaman, Giovanni Neglia

Knowledge Graphs Can be Learned with Just Intersection Features

Duy Le, Shaochen Zhong, Zirui Liu, Shuai Xu, Vipin Chaudhary

Robust Inverse Graphics via Probabilistic Inference

Tuan Anh Le, Pavel Sountsov, Matthew Douglas Hoffman, Ben Lee, Brian Patton

Generalized Sobolev Transport for Probability Measures on a Graph

Tam Le, Truyen Nguyen, Kenji Fukumizu

Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms

Filippo Lazzati, Mirco Mutti, Alberto Maria Metelli

Modeling Caption Diversity in Contrastive Vision-Language Pretraining

Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mido Assran, Andrew Gordon Wilson

Towards Understanding Inductive Bias in Transformers: A View From Infinity

Itay Lavie, Guy Gur-Ari, Zohar Ringel

Single-Model Attribution of Generative Models Through Final-Layer Inversion

Mike Laszkiewicz, Jonas Ricker, Johannes Lederer, Asja Fischer

Sub-token ViT Embedding via Stochastic Resonance Transformers

DONG LAO, Yangchao Wu, Tian Yu Liu, Alex Wong, Stefano Soatto

A Neural-Preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions

Kai Weixian Lan, Elias Gueidon, Ayano Kaneda, Julian Panetta, Joseph Teran

Privately Learning Smooth Distributions on the Hypercube by Projections

Clément Lalanne, Sébastien Gadat

Invariant Risk Minimization Is A Total Variation Model

Zhao-Rong Lai, Weiwen Wang

Position: Evolving AI Collectives Enhance Human Diversity and Enable Self-Regulation

Shiyang Lai, Yujin Potter, Junsol Kim, Richard Zhuang, Dawn Song

Collective Certified Robustness against Graph Injection Attacks

Yuni Lai, Bailin Pan, Kaihuang Chen, Yancheng Yuan, Kai Zhou

Dynamic Spectral Clustering with Provable Approximation Guarantee

Steinar Laenen, He Sun

TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge

Young D. Kwon, Rui Li, Stylianos Venieris, Jagmohan Chauhan, Nicholas Donald Lane

On The Complexity of First-Order Methods in Stochastic Bilevel Optimization

Jeongyeol Kwon, Dohyun Kwon, Hanbaek Lyu

Prospective Side Information for Latent MDPs

Jeongyeol Kwon, Yonathan Efroni, Shie Mannor, Constantine Caramanis

Minimum Norm Interpolation Meets The Local Theory of Banach Spaces

Gil Kur, Pedro Abdalla, Pierre Bizeul, Fanny Yang

Efficient Value Iteration for s-rectangular Robust Markov Decision Processes

Navdeep Kumar, KAIXIN WANG, Kfir Yehuda Levy, Shie Mannor

No Free Prune: Information-Theoretic Barriers to Pruning at Initialization

Tanishq Kumar, Kevin Luo, Mark Sellke

Mean Estimation in the Add-Remove Model of Differential Privacy

Alex Kulesza, Ananda Theertha Suresh, Yuyan Wang

Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph

Yufei Kuang, Jie Wang, Yuyan Zhou, Xijun Li, Fangzhou Zhu

A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?

Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta, Pascal Poupart, Alan Aspuru-Guzik

Understanding the Effects of Iterative Prompting on Truthfulness

Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju

Geometry-Aware Instrumental Variable Regression

Heiner Kremer, Bernhard Schölkopf

Implicit meta-learning may lead language models to trust more reliable sources

Dmitrii Krasheninnikov, Egor Krasheninnikov, Bruno Kacper Mlodozeniec, Tegan Maharaj, David Krueger

Sobolev Space Regularised Pre Density Models

Mark Kozdoba, Binyamin Perets, Shie Mannor

PcLast: Discovering Plannable Continuous Latent States

Anurag Koul, Shivakanth Sujit, Shaoru Chen, Ben Evans, Lili Wu

KISA: A Unified Keyframe Identifier and Skill Annotator for Long-Horizon Robotics Demonstrations

Longxin Kou, Fei Ni, YAN ZHENG, Jinyi Liu, Yifu Yuan

CLLMs: Consistency Large Language Models

Siqi Kou, Lanxiang Hu, Zhezhi He, Zhijie Deng, Hao Zhang

A General Online Algorithm for Optimizing Complex Performance Metrics

Wojciech Kotlowski, Marek Wydmuch, Erik Schultheis, Rohit Babbar, Krzysztof Dembczynski

Consistent Long-Term Forecasting of Ergodic Dynamical Systems

Vladimir R Kostic, Karim Lounici, Prune Inzerilli, Pietro Novelli, Massimiliano Pontil

Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks

Atli Kosson, Bettina Messmer, Martin Jaggi

Privacy Profiles for Private Selection

Antti Koskela, Rachel Emily Redberg, Yu-Xiang Wang

convSeq: Fast and Scalable Method for Detecting Patterns in Spike Data

Roman Koshkin, Tomoki Fukai

Bridging Mini-Batch and Asymptotic Analysis in Contrastive Learning: From InfoNCE to Kernel-Based Losses

Panagiotis Koromilas, Giorgos Bouritsas, Theodoros Giannakopoulos, Mihalis Nicolaou, Yannis Panagakis

Understanding and Diagnosing Deep Reinforcement Learning

Ezgi Korkmaz