ICML 2024

2,610 papers

Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?

Mira Juergens, Nis Meinert, Viktor Bengs, Eyke Hüllermeier, Willem Waegeman

NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models

Zeqian Ju, Yuancheng Wang, Kai Shen, Xu Tan, Detai Xin

Hypergraph-enhanced Dual Semi-supervised Graph Classification

Wei Ju, Zhengyang Mao, Siyu Yi, Yifang Qin, Yiyang Gu

Watermark Stealing in Large Language Models

Nikola Jovanović, Robin Staab, Martin Vechev

Position: Benchmarking is Limited in Reinforcement Learning Research

Scott M. Jordan, Adam White, Bruno Castro da Silva, Martha White, Philip S. Thomas

Decoupling Feature Extraction and Classification Layers for Calibrated Neural Networks

Mikkel Jordahn, Pablo M. Olmos

IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation

Taejong Joo, Diego Klabjan

Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning

Arvi Jonnarth, Jie Zhao, Michael Felsberg

Learning to Infer Generative Template Programs for Visual Concepts

R. Kenny Jones, Siddhartha Chaudhuri, Daniel Ritchie

Experts Don’t Cheat: Learning What You Don’t Know By Predicting Pairs

Daniel D. Johnson, Daniel Tarlow, David Duvenaud, Chris J. Maddison

Graph Generation with Diffusion Mixture

Jaehyeong Jo, Dongki Kim, Sung Ju Hwang

Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes

Jaehyeong Jo, Sung Ju Hwang

Model-Based Minimum Bayes Risk Decoding for Text Generation

Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe

FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data

Shusen Jing, Anlan Yu, SHUAI ZHANG, Songyang Zhang

AlphaFold Meets Flow Matching for Generating Protein Ensembles

Bowen Jing, Bonnie Berger, Tommi Jaakkola

Position: What Can Large Language Models Tell Us about Time Series Analysis

Ming Jin, Yifan Zhang, Wei Chen, KeXin Zhang, Yuxuan Liang

Language Models as Semantic Indexers

Bowen Jin, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei

An Image is Worth Multiple Words: Discovering Object Level Concepts using Multi-Concept Prompt Learning

Chen Jin, Ryutaro Tanno, Amrutha Saseendran, Tom Diethe, Philip Alexander Teare

Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization

Yang Jin, Zhicheng Sun, Kun Xu, Liwei Chen, Hao Jiang

Emergent Representations of Program Semantics in Language Models Trained on Programs

Charles Jin, Martin Rinard

What Will My Model Forget? Forecasting Forgotten Examples in Language Model Refinement

Xisen Jin, Xiang Ren

On the Maximal Local Disparity of Fairness-Aware Classifiers

Jinqiu Jin, Haoxuan Li, Fuli Feng

LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning

Hongye Jin, Xiaotian Han, Jingfeng Yang, Zhimeng Jiang, Zirui Liu

Homomorphism Counts for Graph Neural Networks: All About That Basis

Emily Jin, Michael M. Bronstein, İsmail İlkan Ceylan, Matthias Lanzinger

Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning

Shibo Jie, Yehui Tang, Ning Ding, Zhi-Hong Deng, Kai Han

SuDA: Support-based Domain Adaptation for Sim2Real Hinge Joint Tracking with Flexible Sensors

Fang Jiawei, Haishan Song, Chengxu Zuo, Xiaoxia Gao, Xiaowei Chen

Generalized Neural Collapse for a Large Number of Classes

Jiachen Jiang, Jinxin Zhou, Peng Wang, Qing Qu, Dustin G. Mixon

Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images

Jun-Peng Jiang, Han-Jia Ye, Leye Wang, Yang Yang, Yuan Jiang

Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization

Wei Jiang, Sifan Yang, Wenhao Yang, Yibo Wang, Yuanyu Wan

HexGen: Generative Inference of Large Language Model over Heterogeneous Environment

YOUHE JIANG, Ran Yan, Xiaozhe Yao, Yang Zhou, Beidi Chen

Federated Optimization with Doubly Regularized Drift Correction

Xiaowen Jiang, Anton Rodomanov, Sebastian U Stich

On the Origins of Linear Representations in Large Language Models

Yibo Jiang, Goutham Rajendran, Pradeep Kumar Ravikumar, Bryon Aragam, Victor Veitch

ProtoGate: Prototype-based Neural Networks with Global-to-local Feature Selection for Tabular Biomedical Data

Xiangjian Jiang, Andrei Margeloiu, Nikola Simidjievski, Mateja Jamnik

Conditional Common Entropy for Instrumental Variable Testing and Partial Identification

Ziwei Jiang, Murat Kocaoglu

NDOT: Neuronal Dynamics-based Online Training for Spiking Neural Networks

Haiyan Jiang, Giulia De Masi, Huan Xiong, Bin Gu

Pre-Training Protein Bi-level Representation Through Span Mask Strategy On 3D Protein Chains

Zhao Jiale, Wanru Zhuang, Jia Song, Yaqi Li, Shuqi Lu

Chain-of-Thought Predictive Control

Zhiwei Jia, Vineet Thumuluri, Fangchen Liu, Linghao Chen, Zhiao Huang

GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer

Ding Jia, Jianyuan Guo, Kai Han, Han Wu, Chao Zhang

Simulation-Based Inference with Quantile Regression

He Jia

Discrete Latent Perspective Learning for Segmentation and Detection

Deyi Ji, Feng Zhao, Lanyun Zhu, Wenwei Jin, Hongtao Lu

Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic

Tianying Ji, Yu Luo, Fuchun Sun, Xianyuan Zhan, Jianwei Zhang

Towards Efficient Exact Optimization of Language Model Alignment

Haozhe Ji, Cheng Lu, Yilin Niu, Pei Ke, Hongning Wang

ACE: Off-Policy Actor-Critic with Causality-Aware Entropy Regularization

Tianying Ji, Yongyuan Liang, Yan Zeng, Yu Luo, Guowei Xu

Advancing Dynamic Sparse Training by Exploring Optimization Opportunities

Jie Ji, Gen Li, Lu Yin, Minghai Qin, Geng Yuan

ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages

Andrew Jesson, Chris Lu, Gunshi Gupta, Nicolas Beltran-Velez, Angelos Filos

Finite Volume Features, Global Geometry Representations, and Residual Training for Deep Learning-based CFD Simulation

Loh Sher En Jessica, Naheed Anjum Arafat, Wei Xian Lim, Wai Lee Chan, Adams Wai-Kin Kong

An Information-Theoretic Analysis of In-Context Learning

Hong Jun Jeon, Jason D. Lee, Qi Lei, Benjamin Van Roy

Repeat After Me: Transformers are Better than State Space Models at Copying

Samy Jelassi, David Brandfonbrener, Sham M. Kakade, Eran Malach

Gradual Divergence for Seamless Adaptation: A Novel Domain Incremental Learning Method

Kishaan Jeeveswaran, Elahe Arani, Bahram Zonooz

Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery

Yassir Jedra, William Réveillard, Stefan Stojanovic, Alexandre Proutiere

PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses

Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni

Bringing Motion Taxonomies to Continuous Domains via GPLVM on Hyperbolic manifolds

Noémie Jaquier, Leonel Rozo, Miguel González-Duque, Viacheslav Borovitskiy, Tamim Asfour

Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits

Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun

LoRA Training in the NTK Regime has No Spurious Local Minima

Uijeong Jang, Jason D. Lee, Ernest K. Ryu

Visual Representation Learning with Stochastic Frame Prediction

Huiwon Jang, Dongyoung Kim, Junsu Kim, Jinwoo Shin, Pieter Abbeel

Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration

Youngsoo Jang, Geon-hyeong Kim, Byoungjip Kim, Yu Jin Kim, Honglak Lee

Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD

Jonggyu Jang, Seongjin Hwang, Hyun Jong Yang

On the sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery

Fateme Jamshidi, Luca Ganassali, Negar Kiyavash

R2E: Turning any Github Repository into a Programming Agent Environment

Naman Jain, Manish Shetty, Tianjun Zhang, King Han, Koushik Sen

Learning to Reach Goals via Diffusion

Vineet Jain, Siamak Ravanbakhsh

Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized

Shomik Jain, Kathleen Creel, Ashia Camage Wilson

Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks

Akshay Kumar Jagadish, Julian Coda-Forno, Mirko Thalmann, Eric Schulz, Marcel Binz

Online Linear Regression in Dynamic Environments via Discounting

Andrew Jacobsen, Ashok Cutkosky

PAGER: Accurate Failure Characterization in Deep Regression Models

Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Puja Trivedi, Rushil Anirudh

Nesting Particle Filters for Experimental Design in Dynamical Systems

Sahel Iqbal, Adrien Corenflos, Simo Särkkä, Hany Abdulsamad

PASOA- PArticle baSed Bayesian Optimal Adaptive design

Jacopo Iollo, Christophe Heinkelé, Pierre Alliez, Florence Forbes

Zero-Shot Reinforcement Learning via Function Encoders

Tyler Ingebrand, Amy Zhang, Ufuk Topcu

Understanding the Learning Dynamics of Alignment with Human Feedback

Shawn Im, Yixuan Li

From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers

Muhammed Emrullah Ildiz, Yixiao Huang, Yingcong Li, Ankit Singh Rawat, Samet Oymak

SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention

Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo

Smooth Min-Max Monotonic Networks

Christian Igel

EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal Tokens

Sunil Hwang, Jaehong Yoon, Youngwan Lee, Sung Ju Hwang

Adapting Pretrained ViTs with Convolution Injector for Visuo-Motor Control

Dongyoon Hwang, Byungkun Lee, Hojoon Lee, HYUNSEUNG KIM, Jaegul Choo

Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning

Inwoo Hwang, Yunhyeok Kwak, Suhyung Choi, Byoung-tak Zhang, Sanghack Lee

On Positivity Condition for Causal Inference

Inwoo Hwang, Yesong Choe, Yeahoon Kwon, Sanghack Lee

Vanilla Bayesian Optimization Performs Great in High Dimensions

Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi

Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers

Md Shamim Hussain, Mohammed J Zaki, Dharmashankar Subramanian

Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models

Mingjia Huo, Sai Ashish Somayajula, Youwei Liang, Ruisi Zhang, Farinaz Koushanfar

Deep Networks Always Grok and Here is Why

Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk

Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians

Tom Huix, Anna Korba, Alain Oliviero Durmus, Eric Moulines

Residual Quantization with Implicit Neural Codebooks

Iris A.M. Huijben, Matthijs Douze, Matthew J. Muckley, Ruud Van Sloun, Jakob Verbeek

Make-A-Shape: a Ten-Million-scale 3D Shape Model

Ka-Hei Hui, Aditya Sanghi, Arianna Rampini, Kamal Rahimi Malekshan, Zhengzhe LIU

Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning

Joon Suk Huh, Kirthevasan Kandasamy

Position: The Platonic Representation Hypothesis

Minyoung Huh, Brian Cheung, Tongzhou Wang, Phillip Isola

Position: Open-Endedness is Essential for Artificial Superhuman Intelligence

Edward Hughes, Michael D Dennis, Jack Parker-Holder, Feryal Behbahani, Aditi Mavalankar

Faster Sampling via Stochastic Gradient Proximal Sampler

Xunpeng Huang, Difan Zou, Hanze Dong, Yian Ma, Tong Zhang

Adversarially Robust Deep Multi-View Clustering: A Novel Attack and Defense Framework

Haonan Huang, Guoxu Zhou, Yanghang Zheng, Yuning Qiu, Andong Wang

Faster Adaptive Decentralized Learning Algorithms

Feihu Huang, Jianyu Zhao

Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge

Yufei Huang, Odin Zhang, Lirong Wu, Cheng Tan, Haitao Lin

InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning

Zhe Huang, Xiaowei Yu, Dajiang Zhu, Michael C Hughes

An Embodied Generalist Agent in 3D World

Jiangyong Huang, Silong Yong, Xiaojian Ma, Xiongkun Linghu, Puhao Li

Triadic-OCD: Asynchronous Online Change Detection with Provable Robustness, Optimality, and Convergence

Yancheng Huang, Kai Yang, Zelin Zhu, Leian Chen

Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning

Zheng Huang, Qihui Yang, Dawei Zhou, Yujun Yan

Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation

Zhilin Huang, Ling Yang, Xiangxin Zhou, Chujun Qin, Yijie Yu

Conformal Prediction for Deep Classifier via Label Ranking

Jianguo Huang, Huajun Xi, Linjun Zhang, Huaxiu Yao, Yue Qiu

How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing

Keke Huang, Yu Guang Wang, Ming Li, Pietro Lió

MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation

Qian Huang, Jian Vora, Percy Liang, Jure Leskovec

Position: TrustLLM: Trustworthiness in Large Language Models

Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang

Quasi-Monte Carlo Features for Kernel Approximation

Zhen Huang, Jiajin Sun, Yian Huang

Overcoming Data and Model heterogeneities in Decentralized Federated Learning via Synthetic Anchors

Chun-Yin Huang, Kartik Srinivas, Xin Zhang, Xiaoxiao Li