ICML 2024

2,610 papers

Understanding MLP-Mixer as a wide and sparse MLP

Tomohiro Hayase, Ryo Karakida

GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements

Alexander Havrilla, Sharath Chandra Raparthy, Christoforos Nalmpantis, Jane Dwivedi-Yu, Maksym Zhuravinskyi

Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer

Doron Haviv, Russell Zhang Kunes, Thomas Dougherty, Cassandra Burdziak, Tal Nawy

Fine-grained Local Sensitivity Analysis of Standard Dot-Product Self-Attention

Aaron J Havens, Alexandre Araujo, Huan Zhang, Bin Hu

Position: $C^*$-Algebraic Machine Learning $-$ Moving in a New Direction

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri

Estimating the Permanent by Nesting Importance Sampling

Juha Harviainen, Mikko Koivisto

Convergence Guarantees for the DeepWalk Embedding on Block Models

Christopher Harker, Aditya Bhaskara

DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training

Zhongkai Hao, Chang Su, Songming Liu, Julius Berner, Chengyang Ying

MGit: A Model Versioning and Management System

Wei Hao, Daniel Mendoza, Rafael Mendes, Deepak Narayanan, Amar Phanishayee

Data-efficient Large Vision Models through Sequential Autoregression

Zhiwei Hao, Jianyuan Guo, Chengcheng Wang, Yehui Tang, Han Wu

Flora: Low-Rank Adapters Are Secretly Gradient Compressors

Yongchang Hao, Yanshuai Cao, Lili Mou

Interpreting Equivariant Representations

Andreas Abildtrup Hansen, Anna Calissano, Aasa Feragen

Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text

Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha

Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning

Jun-Yi Hang, Min-ling Zhang

Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference

Yujin Han, Difan Zou

Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning

Sungwon Han, Jinsung Yoon, Sercan O Arik, Tomas Pfister

SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting

Lu Han, Han-Jia Ye, De-Chuan Zhan

Prototypical Transformer As Unified Motion Learners

Cheng Han, Yawen Lu, Guohao Sun, James Chenhao Liang, Zhiwen Cao

Riemannian coordinate descent algorithms on matrix manifolds

Andi Han, Pratik Jawanpuria, Bamdev Mishra

Model Assessment and Selection under Temporal Distribution Shift

Elise Han, Chengpiao Huang, Kaizheng Wang

UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs

Xi Han, Fei Hou, Hong Qin

Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming

Hany Hamed, Subin Kim, Dongyeong Kim, Jaesik Yoon, Sungjin Ahn

A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle

Nadav Hallak, Kfir Yehuda Levy

Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation

Danny Halawi, Alexander Wei, Eric Wallace, Tony Tong Wang, Nika Haghtalab

Incorporating probabilistic domain knowledge into deep multiple instance learning

Ghadi S. Al Hajj, Aliaksandr Hubin, Chakravarthi Kanduri, Milena Pavlović, Knut Dagestad Rand

Pursuing Overall Welfare in Federated Learning through Sequential Decision Making

Seok-Ju Hahn, Gi-Soo Kim, Junghye Lee

Isometric Representation Learning for Disentangled Latent Space of Diffusion Models

Jaehoon Hahm, Junho Lee, Sunghyun Kim, Joonseok Lee

Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations

Jan Hagnberger, Marimuthu Kalimuthu, Daniel Musekamp, Mathias Niepert

Optimally Improving Cooperative Learning in a Social Setting

Shahrzad Haddadan, Cheng Xin, Jie Gao

Robust Yet Efficient Conformal Prediction Sets

Soroush H. Zargarbashi, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski

Light and Optimal Schrödinger Bridge Matching

Nikita Gushchin, Sergei Kholkin, Evgeny Burnaev, Alexander Korotin

GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks

Shivanshu Gupta, Clemens Rosenbaum, Ethan R. Elenberg

xT: Nested Tokenization for Larger Context in Large Images

Ritwik Gupta, Shufan Li, Tyler Zhu, Jitendra Malik, Trevor Darrell

Diffusion Posterior Sampling is Computationally Intractable

Shivam Gupta, Ajil Jalal, Aditya Parulekar, Eric Price, Zhiyang Xun

Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning

Zijian Guo, Weichao Zhou, Wenchao Li

COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability

Xingang Guo, Fangxu Yu, Huan Zhang, LIANHUI Qin, Bin Hu

Automated Loss function Search for Class-imbalanced Node Classification

Xinyu Guo, Kai WU, Xiaoyu Zhang, Jing Liu

Compressing Large Language Models by Joint Sparsification and Quantization

Jinyang Guo, Jianyu Wu, Zining Wang, Jiaheng Liu, Ge Yang

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering

Yongxin Guo, Xiaoying Tang, Tao LIN

On the Embedding Collapse when Scaling up Recommendation Models

Xingzhuo Guo, Junwei Pan, Ximei Wang, Baixu Chen, Jie Jiang

ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation

Ziao Guo, Yang Li, Chang Liu, Wenli Ouyang, Junchi Yan

Collaborative Heterogeneous Causal Inference Beyond Meta-analysis

Tianyu Guo, Sai Praneeth Karimireddy, Michael Jordan

DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning

Siyuan Guo, Cheng Deng, Ying Wen, Hechang Chen, Yi Chang

SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization

Jialong Guo, Xinghao Chen, Yehui Tang, Yunhe Wang

Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation

Gauthier Guinet, Behrooz Omidvar-Tehrani, Anoop Deoras, Laurent Callot

No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths

Charles Guille-Escuret, Hiroki Naganuma, Kilian Fatras, Ioannis Mitliagkas

Vector Quantization Pretraining for EEG Time Series with Random Projection and Phase Alignment

Haokun Gui, Xiucheng Li, Xinyang Chen

On the Diminishing Returns of Width for Continual Learning

Etash Kumar Guha, Vihan Lakshman

Predictive Performance Comparison of Decision Policies Under Confounding

Luke Guerdan, Amanda Lee Coston, Ken Holstein, Steven Wu

Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast

Xiangming Gu, Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu

Data-free Distillation of Diffusion Models with Bootstrapping

Jiatao Gu, Chen Wang, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu

CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution

Alex Gu, Baptiste Roziere, Hugh James Leather, Armando Solar-Lezama, Gabriel Synnaeve

EDISON: Enhanced Dictionary-Induced Tensorized Incomplete Multi-View Clustering with Gaussian Error Rank Minimization

Zhibin Gu, Zhendong Li, Songhe Feng

On the Calibration of Human Pose Estimation

Kerui Gu, Rongyu Chen, Xuanlong Yu, Angela Yao

Overcoming Saturation in Density Ratio Estimation by Iterated Regularization

Lukas Gruber, Markus Holzleitner, Johannes Lehner, Sepp Hochreiter, Werner Zellinger

A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models

Sebastian Gregor Gruber, Florian Buettner

Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features Critics

Luca Grillotti, Maxence Faldor, Borja G. Leon, Antoine Cully

Scaling Down Deep Learning with MNIST-1D

Samuel James Greydanus, Dmitry Kobak

A Bayesian Approach to Online Planning

Nir Greshler, David Ben Eli, Carmel Rabinovitz, Gabi Guetta, Liran Gispan

Stochastic Localization via Iterative Posterior Sampling

Louis Grenioux, Maxence Noble, Marylou Gabrie, Alain Oliviero Durmus

AI Control: Improving Safety Despite Intentional Subversion

Ryan Greenblatt, Buck Shlegeris, Kshitij Sachan, Fabien Roger

Fine-grained Classes and How to Find Them

Matej Grcić, Artyom Gadetsky, Maria Brbic

Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates

Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo

The Expressive Power of Path-Based Graph Neural Networks

Caterina Graziani, Tamara Drucks, Fabian Jogl, Monica Bianchini, Franco Scarselli

Long Range Propagation on Continuous-Time Dynamic Graphs

Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio, Davide Bacciu, Claas Grohnfeldt

Learning Universal Predictors

Jordi Grau-moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang

Test-Time Degradation Adaptation for Open-Set Image Restoration

Yuanbiao Gou, Haiyu Zhao, Boyun Li, Xinyan Xiao, Xi Peng

Weighted distance nearest neighbor condensing

Lee-Ad Gottlieb, Timor Sharabi, Roi Weiss

MOMENT: A Family of Open Time-series Foundation Models

Mononito Goswami, Konrad Szafer, Arjun Choudhry, Yifu Cai, Shuo Li

Out-of-Domain Generalization in Dynamical Systems Reconstruction

Niclas Alexander Göring, Florian Hess, Manuel Brenner, Zahra Monfared, Daniel Durstewitz

High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise

Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova, Samuel Horváth, Gauthier Gidel

E$^2$GAN: Efficient Training of Efficient GANs for Image-to-Image Translation

Yifan Gong, Zheng Zhan, Qing Jin, Yanyu Li, Yerlan Idelbayev

Evaluation of LLMs on Syntax-Aware Code Fill-in-the-Middle Tasks

Linyuan Gong, Sida Wang, Mostafa Elhoushi, Alvin Cheung

Evolution-Inspired Loss Functions for Protein Representation Learning

Chengyue Gong, Adam Klivans, James Madigan Loy, Tianlong Chen, Qiang Liu

A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness

Xiaochuan Gong, Jie Hao, Mingrui Liu

AST-T5: Structure-Aware Pretraining for Code Generation and Understanding

Linyuan Gong, Mostafa Elhoushi, Alvin Cheung

Does Label Smoothing Help Deep Partial Label Learning?

Xiuwen Gong, Nitin Bisht, Guandong Xu

CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling

Junchao Gong, LEI BAI, Peng Ye, Wanghan Xu, Na Liu

Position: The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning

Micah Goldblum, Marc Anton Finzi, Keefer Rowan, Andrew Gordon Wilson

Position: Fundamental Limitations of LLM Censorship Necessitate New Approaches

David Glukhov, Ilia Shumailov, Yarin Gal, Nicolas Papernot, Vardan Papyan

All-in-one simulation-based inference

Manuel Gloeckler, Michael Deistler, Christian Dietrich Weilbach, Frank Wood, Jakob H. Macke

Better & Faster Large Language Models via Multi-token Prediction

Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Roziere, David Lopez-paz, Gabriel Synnaeve

Kernel-Based Evaluation of Conditional Biological Sequence Models

Pierre Glaser, Steffanie Paul, Alissa M Hummer, Charlotte Deane, Debora Susan Marks

Self-Correcting Self-Consuming Loops for Generative Model Training

Nate Gillman, Michael Freeman, Daksh Aggarwal, Chia-Hong Hsu, Calvin Luo

Optimal Eye Surgeon: Finding image priors through sparse generators at initialization

Avrajit Ghosh, Xitong Zhang, Kenneth K. Sun, Qing Qu, Saiprasad Ravishankar

Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms

Avishek Ghosh, Arya Mazumdar

A Closer Look at the Limitations of Instruction Tuning

Sreyan Ghosh, Chandra Kiran Reddy Evuru, Sonal Kumar, Ramaneswaran S, Deepali Aneja

Understanding Finetuning for Factual Knowledge Extraction

Gaurav Rohit Ghosal, Tatsunori Hashimoto, Aditi Raghunathan

State-Constrained Zero-Sum Differential Games with One-Sided Information

Mukesh Ghimire, Lei Zhang, Zhe Xu, Yi Ren

Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon

Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models

Asma Ghandeharioun, Avi Caciularu, Adam Pearce, Lucas Dixon, Mor Geva

Emergent Equivariance in Deep Ensembles

Jan E Gerken, Pan Kessel

Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation

Ignat Georgiev, Krishnan Srinivasan, Jie Xu, Eric Heiden, Animesh Garg

Reinforcement Learning within Tree Search for Fast Macro Placement

Zijie Geng, Jie Wang, Ziyan Liu, Siyuan Xu, Zhentao Tang

Improving Adversarial Energy-Based Model via Diffusion Process

Cong Geng, Tian Han, Peng-tao Jiang, Hao Zhang, Jinwei Chen

Graph-Triggered Rising Bandits

Gianmarco Genalti, Marco Mussi, Nicola Gatti, Marcello Restelli, Matteo Castiglioni

Learning with 3D rotations, a hitchhiker’s guide to SO(3)

Andreas René Geist, Jonas Frey, Mikel Zhobro, Anna Levina, Georg Martius

Don’t trust your eyes: on the (un)reliability of feature visualizations

Robert Geirhos, Roland S. Zimmermann, Blair Bilodeau, Wieland Brendel, Been Kim

No Double Descent in Principal Component Regression: A High-Dimensional Analysis

Daniel Gedon, Antônio H. Ribeiro, Thomas B. Schön

Safe and Robust Subgame Exploitation in Imperfect Information Games

Zhenxing Ge, Zheng Xu, Tianyu Ding, Linjian Meng, Bo An