ICML 2024

2,610 papers

Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective

Fabian Falck, Ziyu Wang, Christopher C. Holmes

DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistency

Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi

Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models

Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi

Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift

Benjamin Eyre, Elliot Creager, David Madras, Vardan Papyan, Richard Zemel

Scaling Exponents Across Parameterizations and Optimizers

Katie E Everett, Lechao Xiao, Mitchell Wortsman, Alexander A Alemi, Roman Novak

Fast Timing-Conditioned Latent Audio Diffusion

Zach Evans, CJ Carr, Josiah Taylor, Scott H. Hawley, Jordi Pons

Model Alignment as Prospect Theoretic Optimization

Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff, Dan Jurafsky, Douwe Kiela

Scaling Rectified Flow Transformers for High-Resolution Image Synthesis

Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller

High-Dimensional Geometric Streaming for Nearly Low Rank Data

Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David Woodruff, Peilin Zhong

PAC-Bayesian Error Bound, via Rényi Divergence, for a Class of Linear Time-Invariant State-Space Models

Deividas Eringis, John Leth, Zheng-Hua Tan, Rafal Wisniewski, Mihaly Petreczky

Disentangled 3D Scene Generation with Layout Learning

Dave Epstein, Ben Poole, Ben Mildenhall, Alexei A Efros, Aleksander Holynski

Compositional Curvature Bounds for Deep Neural Networks

Taha Entesari, Sina Sharifi, Mahyar Fazlyab

DsDm: Model-Aware Dataset Selection with Datamodels

Logan Engstrom, Axel Feldmann, Aleksander Madry

Approximate Nearest Neighbor Search with Window Filters

Joshua Engels, Ben Landrum, Shangdi Yu, Laxman Dhulipala, Julian Shun

Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning

Mohamed Elsayed, Homayoon Farrahi, Felix Dangel, A. Rupam Mahmood

Neuro-Visualizer: A Novel Auto-Encoder-Based Loss Landscape Visualization Method With an Application in Knowledge-Guided Machine Learning

Mohannad Elhamod, Anuj Karpatne

TSLANet: Rethinking Transformers for Time Series Representation Learning

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Xiaoli Li

Adaptive Online Experimental Design for Causal Discovery

Muhammad Qasim Elahi, Lai Wei, Murat Kocaoglu, Mahsa Ghasemi

Scalable Pre-training of Large Autoregressive Image Models

Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Angel Bautista, Vaishaal Shankar

Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI

Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schroeder de Witt, Fabio Pizzati

Efficient Error Certification for Physics-Informed Neural Networks

Francisco Eiras, Adel Bibi, Rudy R Bunel, Krishnamurthy Dj Dvijotham, Philip Torr

Ai-sampler: Adversarial Learning of Markov kernels with involutive maps

Evgenii Egorov, Riccardo Valperga, Stratis Gavves

Extreme Compression of Large Language Models via Additive Quantization

Vage Egiazarian, Andrei Panferov, Denis Kuznedelev, Elias Frantar, Artem Babenko

Position: Insights from Survey Methodology can Improve Training Data

Stephanie Eckman, Barbara Plank, Frauke Kreuter

Equivariant Frames and the Impossibility of Continuous Canonicalization

Nadav Dym, Hannah Lawrence, Jonathan W. Siegel

Efficient Exploration for LLMs

Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao, Benjamin Van Roy

Barrier Algorithms for Constrained Non-Convex Optimization

Pavel Dvurechensky, Mathias Staudigl

Enabling Uncertainty Estimation in Iterative Neural Networks

Nikita Durasov, Doruk Oner, Jonathan Donier, Hieu Le, Pascal Fua

Outlier-robust Kalman Filtering through Generalised Bayes

Gerardo Duran-Martin, Matias Altamirano, Alex Shestopaloff, Leandro Sánchez-Betancourt, Jeremias Knoblauch

Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation

Benjamin Dupuis, Umut Simsekli

Making Old Things New: A Unified Algorithm for Differentially Private Clustering

Max Dupré la Tour, Monika Henzinger, David Saulpic

Sharpness-Aware Data Generation for Zero-shot Quantization

Hoang Anh Dung, Cuong Pham, Trung Le, Jianfei Cai, Thanh-Toan Do

Observable Propagation: Uncovering Feature Vectors in Transformers

Jacob Dunefsky, Arman Cohan

Consistent Submodular Maximization

Paul Duetting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard, Morteza Zadimoghaddam

Unveiling the Potential of AI for Nanomaterial Morphology Prediction

Ivan Dubrovsky, Andrei Dmitrenko, Aleksei Dmitrenko, Nikita Serov, Vladimir Vinogradov

DE-COP: Detecting Copyrighted Content in Language Models Training Data

Andre Vicente Duarte, Xuandong Zhao, Arlindo L. Oliveira, Lei Li

MF-CLR: Multi-Frequency Contrastive Learning Representation for Time Series

Jufang Duan, Wei Zheng, Yangzhou Du, Wenfa Wu, Haipeng Jiang

MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving

Jiangfei Duan, Runyu Lu, Haojie Duanmu, Xiuhong Li, Xingcheng Zhang

Bottleneck-Minimal Indexing for Generative Document Retrieval

Xin Du, Lixin Xiu, Kumiko Tanaka-Ishii

Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization

Yihan Du, Anna Winnicki, Gal Dalal, Shie Mannor, R. Srikant

AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls

Yu Du, Fangyun Wei, Hongyang Zhang

When and How Does In-Distribution Label Help Out-of-Distribution Detection?

Xuefeng Du, Yiyou Sun, Yixuan Li

Learning Iterative Reasoning through Energy Diffusion

Yilun Du, Jiayuan Mao, Joshua B. Tenenbaum

Improving Factuality and Reasoning in Language Models through Multiagent Debate

Yilun Du, Shuang Li, Antonio Torralba, Joshua B. Tenenbaum, Igor Mordatch

Position: Compositional Generative Modeling: A Single Model is Not All You Need

Yilun Du, Leslie Pack Kaelbling

GliDe with a CaPE: A Low-Hassle Method to Accelerate Speculative Decoding

Cunxiao Du, Jing Jiang, Xu Yuanchen, Jiawei Wu, Sicheng Yu

SimPro: A Simple Probabilistic Framework Towards Realistic Long-Tailed Semi-Supervised Learning

Chaoqun Du, Yizeng Han, Gao Huang

Principled Gradient-Based MCMC for Conditional Sampling of Text

Li Du, Afra Amini, Lucas Torroba Hennigen, Xinyan Velocity Yu, Holden Lee

WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?

Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme

On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows

Felix Draxler, Stefan Wahl, Christoph Schnoerr, Ullrich Koethe

Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling

Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang

Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs

Jordan Dotzel, Yuzong Chen, Bahaa Kotb, Sushma Prasad, Gang Wu

Don’t Label Twice: Quantity Beats Quality when Comparing Binary Classifiers on a Budget

Florian E. Dorner, Moritz Hardt

Dynamic Byzantine-Robust Learning: Adapting to Switching Byzantine Workers

Ron Dorfman, Naseem Amin Yehya, Kfir Yehuda Levy

Spike Distance Function as a Learning Objective for Spike Prediction

Kevin Doran, Marvin Seifert, Carola A. M. Yovanovich, Tom Baden

Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent

Konstantin Donhauser, Javier Abad, Neha Hulkund, Fanny Yang

Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference

Harry Dong, Xinyu Yang, Zhenyu Zhang, Zhangyang Wang, Yuejie Chi

TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling

Jiaxiang Dong, Haixu Wu, Yuxuan Wang, Yun-Zhong Qiu, Li Zhang

Accelerating PDE Data Generation via Differential Operator Action in Solution Space

Huanshuo Dong, Hong Wang, Haoyang Liu, Jian Luo, Jie Wang

Position: Building Guardrails for Large Language Models Requires Systematic Design

Yi Dong, Ronghui Mu, Gaojie Jin, Yi Qi, Jinwei Hu

Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models

Peijie Dong, Lujun Li, Zhenheng Tang, Xiang Liu, Xinglin Pan

Towards Generalization beyond Pointwise Learning: A Unified Information-theoretic Perspective

Yuxin Dong, Tieliang Gong, Hong Chen, Zhongjiang He, Mengxiang Li

Impact of Decentralized Learning on Player Utilities in Stackelberg Games

Kate Donahue, Nicole Immorlica, Meena Jagadeesan, Brendan Lucier, Aleksandrs Slivkins

Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions

Nikita Doikov, Sebastian U Stich, Martin Jaggi

Precise Accuracy / Robustness Tradeoffs in Regression: Case of General Norms

Elvis DOHMATOB, meyer scetbon

A Tale of Tails: Model Collapse as a Change of Scaling Laws

Elvis DOHMATOB, Yunzhen Feng, Pu Yang, Francois Charton, Julia Kempe

Consistent Adversarially Robust Linear Classification: Non-Parametric Setting

Elvis DOHMATOB

Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds

Daniel Dodd, Louis Sharrock, Christopher Nemeth

LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, Yuanyuan Xu, Ning Shang

Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization

Li Ding, Jenny Zhang, Jeff Clune, Lee Spector, Joel Lehman

Delving into Differentially Private Transformer

Youlong Ding, Xueyang Wu, Yining Meng, Yonggang Luo, Hao Wang

Fewer Truncations Improve Language Modeling

Hantian Ding, Zijian Wang, Giovanni Paolini, Varun Kumar, Anoop Deoras

Robust Stable Spiking Neural Networks

Jianhao Ding, Zhiyu Pan, Yujia Liu, Zhaofei Yu, Tiejun Huang

Recurrent Distance Filtering for Graph Representation Learning

Yuhui Ding, Antonio Orvieto, Bobby He, Thomas Hofmann

Understanding Forgetting in Continual Learning with Linear Regression

Meng Ding, Kaiyi Ji, Di Wang, Jinhui Xu

AMPA: Adaptive Mixed Precision Allocation for Low-Bit Integer Training

Li Ding, Wen Fei, Yuyang Huang, Shuangrui Ding, Wenrui Dai

Efficient Algorithms for Sum-Of-Minimum Optimization

Lisang Ding, Ziang Chen, Xinshang Wang, Wotao Yin

Structure Your Data: Towards Semantic Graph Counterfactuals

Angeliki Dimitriou, Maria Lymperaiou, Georgios Filandrianos, Konstantinos Thomas, Giorgos Stamou

Convex and Bilevel Optimization for Neural-Symbolic Inference and Learning

Charles Andrew Dickens, Changyu Gao, Connor Pryor, Stephen Wright, Lise Getoor

Fast Co-Training under Weak Dependence via Stream-Based Active Learning

Ilias Diakonikolas, Mingchen Ma, Lisheng Ren, Christos Tzamos

Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination

Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas

Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient

Hao Di, Haishan Ye, Yueling Zhang, Xiangyu Chang, Guang Dai

Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods

Hao Di, Haishan Ye, Xiangyu Chang, Guang Dai, Ivor Tsang

Trust Regions for Explanations via Black-Box Probabilistic Certification

Amit Dhurandhar, Swagatam Haldar, Dennis Wei, Karthikeyan Natesan Ramamurthy

Bivariate Causal Discovery using Bayesian Model Selection

Anish Dhir, Samuel Power, Mark van der Wilk

Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies

Alex Deweese, Guannan Qu

Stability and Multigroup Fairness in Ranking with Uncertain Predictions

Siddartha Devic, Aleksandra Korolova, David Kempe, Vatsal Sharan

Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning

Jannik Deuschel, Caleb Ellington, Yingtao Luo, Ben Lengerich, Pascal Friederich

Multicalibration for Confidence Scoring in LLMs

Gianluca Detommaso, Martin Andres Bertran, Riccardo Fogliato, Aaron Roth

Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations

Justin Deschenaux, Igor Krawczuk, Grigorios Chrysos, Volkan Cevher

Network Tight Community Detection

Jiayi Deng, Xiaodong Yang, Jun Yu, Jun Liu, Zhaiming Shen

Exploring the Low-Pass Filtering Behavior in Image Super-Resolution

Haoyu Deng, Zijing Xu, Yule Duan, Xiao Wu, Wenjie Shu

Collaborative Learning with Different Labeling Functions

Yuyang Deng, Mingda Qiao

Variational Schrödinger Diffusion Models

Wei Deng, Weijian Luo, Yixin Tan, Marin Biloš, Yu Chen

A3S: A General Active Clustering Method with Pairwise Constraints

Xun Deng, Junlong Liu, Han Zhong, Fuli Feng, Chen Shen

Multi-group Learning for Hierarchical Groups

Samuel Deng, Daniel Hsu

An Unsupervised Approach for Periodic Source Detection in Time Series

Berken Utku Demirel, Christian Holz

Prediction-powered Generalization of Causal Inferences

Ilker Demirel, Ahmed Alaa, Anthony Philippakis, David Sontag

Predicting Lagrangian Multipliers for Mixed Integer Linear Programs

Francesco Demelas, Joseph Le Roux, Mathieu Lacroix, Axel Parmentier

Asymptotically Optimal and Computationally Efficient Average Treatment Effect Estimation in A/B testing

Vikas Deep, Achal Bassamboo, Sandeep Kumar Juneja