ICML 2024

2,610 papers

Position: Graph Foundation Models Are Already Here

Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma

Large Language Models are Geographically Biased

Rohin Manvi, Samar Khanna, Marshall Burke, David B. Lobell, Stefano Ermon

Submodular framework for structured-sparse optimal transport

Piyushi Manupriya, Pratik Jawanpuria, Karthik S. Gurumoorthy, Sakethanath Jagarlapudi, Bamdev Mishra

Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion

Hila Manor, Tomer Michaeli

Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks

Stefano Sarao Mannelli, Yaraslau Ivashynka, Andrew M Saxe, Luca Saglietti

Minimum-Norm Interpolation Under Covariate Shift

Neil Rohit Mallinar, Austin Zane, Spencer Frei, Bin Yu

COPAL: Continual Pruning in Large Language Generative Models

Srikanth Malla, Joon Hee Choi, Chiho Choi

Measures of diversity and space-filling designs for categorical data

Cedric Malherbe, Emilio Domı́nguez-Sánchez, Merwan Barlier, Igor Colin, Haitham Bou Ammar

Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning

Saber Malekmohammadi, Yaoliang Yu, Yang Cao

Self-Composing Policies for Scalable Continual Reinforcement Learning

Mikel Malagon, Josu Ceberio, Jose A. Lozano

Auto-Regressive Next-Token Predictors are Universal Learners

Eran Malach

LASER: Linear Compression in Wireless Distributed Optimization

Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim

Position: Data-driven Discovery with Large Generative Models

Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, Sanchaita Hazra, Ashish Sabharwal

SCoRe: Submodular Combinatorial Representation Learning

Anay Majee, Suraj Nandkishor Kothawade, Krishnateja Killamsetty, Rishabh K Iyer

tinyBenchmarks: evaluating LLMs with fewer examples

Felipe Maia Polo, Lucas Weber, Leshem Choshen, Yuekai Sun, Gongjun Xu

Split-and-Denoise: Protect large language model inference with local differential privacy

Peihua Mai, Ran Yan, Zhe Huang, Youjia Yang, Yan Pang

Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games

Yannik Mahlau, Frederik Schubert, Bodo Rosenhahn

Random Latent Exploration for Deep Reinforcement Learning

Srinath V. Mahankali, Zhang-Wei Hong, Ayush Sekhari, Alexander Rakhlin, Pulkit Agrawal

On the Hardness of Probabilistic Neurosymbolic Learning

Jaron Maene, Vincent Derkinderen, Luc De Raedt

Faithfulness Measurable Masked Language Models

Andreas Madsen, Siva Reddy, Sarath Chandar

Unsupervised Parameter-free Simplicial Representation Learning with Scattering Transforms

Hiren Madhu, Sravanthi Gurugubelli, Sundeep Prabhakar Chepuri

Prospector Heads: Generalized Feature Attribution for Large Models & Data

Gautam Machiraju, Alexander Derry, Arjun D Desai, Neel Guha, Amir-Hossein Karimi

A Provable Decision Rule for Out-of-Distribution Detection

Xinsong Ma, Xin Zou, Weiwei Liu

Correcting Diffusion-Based Perceptual Image Compression with Privileged End-to-End Decoder

Yiyang Ma, Wenhan Yang, Jiaying Liu

The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling

Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu

SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment

Ziping Ma, Furong Xu, Jian Liu, Ming Yang, Qingpei Guo

High-dimensional Linear Bandits with Knapsacks

Wanteng Ma, Dong Xia, Jiashuo Jiang

HarmonyDream: Task Harmonization Inside World Models

Haoyu Ma, Jialong Wu, Ningya Feng, Chenjun Xiao, Dong Li

Fast Peer Adaptation with Context-aware Exploration

Long Ma, Yuanfei Wang, Fangwei Zhong, Song-chun Zhu, Yizhou Wang

LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery

Pingchuan Ma, Tsun-Hsuan Wang, Minghao Guo, Zhiqing Sun, Joshua B. Tenenbaum

Reward Shaping for Reinforcement Learning with An Assistant Reward Agent

Haozhe Ma, Kuankuan Sima, Thanh Vinh Vo, Di Fu, Tze-Yun Leong

CKGConv: General Graph Convolution with Continuous Kernels

Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou, Yingxue Zhang

Differentiable Distributionally Robust Optimization Layers

Xutao Ma, Chao Ning, Wenli Du

Do Transformer World Models Give Better Policy Gradients?

Michel Ma, Tianwei Ni, Clement Gehring, Pierluca D’Oro, Pierre-Luc Bacon

Neighboring Perturbations of Knowledge Editing on Large Language Models

Jun-Yu Ma, Zhen-Hua Ling, Ningyu Zhang, Jia-Chen Gu

X-Oscar: A Progressive Framework for High-quality Text-guided 3D Animatable Avatar Generation

Yiwei Ma, Zhekai Lin, Jiayi Ji, Yijun Fan, Xiaoshuai Sun

Outlier-aware Slicing for Post-Training Quantization in Vision Transformer

Yuexiao Ma, Huixia Li, Xiawu Zheng, Feng Ling, Xuefeng Xiao

Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients

Mengmeng Ma, Tang Li, Xi Peng

Learning Modality Knowledge Alignment for Cross-Modality Transfer

Wenxuan Ma, Shuang Li, lincan Cai, Jingxuan Kang

Better Locally Private Sparse Estimation Given Multiple Samples Per User

Yuheng Ma, Ke Jia, Hanfang Yang

Rethinking Decision Transformer via Hierarchical Reinforcement Learning

Yi Ma, Jianye Hao, Hebin Liang, Chenjun Xiao

Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation

Xinyu Ma, Xu Chu, Zhibang Yang, Yang Lin, Xin Gao

Sampling is as easy as keeping the consistency: convergence guarantee for Consistency Models

Junlong Lyu, Zhitang Chen, Shoubo Feng

Cross-Domain Policy Adaptation by Capturing Representation Mismatch

Jiafei Lyu, Chenjia Bai, Jing-Wen Yang, Zongqing Lu, Xiu Li

Efficient and Effective Time-Series Forecasting with Spiking Neural Networks

Changze Lv, Yansen Wang, Dongqi Han, Xiaoqing Zheng, Xuanjing Huang

Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models

Qitan Lv, Jie Wang, Hanzhu Chen, Bin Li, Yongdong Zhang

Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data

Wenxi Lv, Qinliang Su, Hai Wan, Hongteng Xu, Wenchao Xu

RoboMP$^2$: A Robotic Multimodal Perception-Planning Framework with Multimodal Large Language Models

Qi Lv, Hao Li, Xiang Deng, Rui Shao, Michael Y Wang

End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations

Lirui Luo, Guoxi Zhang, Hongming Xu, Yaodong Yang, Cong Fang

Cluster-Aware Similarity Diffusion for Instance Retrieval

Jifei Luo, Hantao Yao, Changsheng Xu

Potential Based Diffusion Motion Planning

Yunhao Luo, Chen Sun, Joshua B. Tenenbaum, Yilun Du

Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution

Xihaier Luo, Xiaoning Qian, Byung-Jun Yoon

Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination

Zhiyao Luo, Yangchen Pan, Peter Watkinson, Tingting Zhu

Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL

Yu Luo, Tianying Ji, Fuchun Sun, Jianwei Zhang, Huazhe Xu

OMPO: A Unified Framework for RL under Policy and Dynamics Shifts

Yu Luo, Tianying Ji, Fuchun Sun, Jianwei Zhang, Huazhe Xu

Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression

Zhankun Luo, Abolfazl Hashemi

PGODE: Towards High-quality System Dynamics Modeling

Xiao Luo, Yiyang Gu, Huiyu Jiang, Hang Zhou, Jinsheng Huang

Projecting Molecules into Synthesizable Chemical Spaces

Shitong Luo, Wenhao Gao, Zuofan Wu, Jian Peng, Connor W. Coley

Scaling Laws for Fine-Grained Mixture of Experts

Jan Ludziejewski, Jakub Krajewski, Kamil Adamczewski, Maciej Pióro, Michał Krutul

SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models

Xudong Lu, Aojun Zhou, Yuhui Xu, Renrui Zhang, peng gao

DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models

Sidi Lu, Wenbo Zhao, Chenyang Tao, Arpit Gupta, Shanchan Wu

OxyGenerator: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning

Bin Lu, Ze Zhao, Luyu Han, Xiaoying Gan, Yuntao Zhou

Disguised Copyright Infringement of Latent Diffusion Models

Yiwei Lu, Matthew Y. R. Yang, Zuoqiu Liu, Gautam Kamath, Yaoliang Yu

Probabilistic Routing for Graph-Based Approximate Nearest Neighbor Search

Kejing Lu, Chuan Xiao, Yoshiharu Ishikawa

FiT: Flexible Vision Transformer for Diffusion Model

Zeyu Lu, Zidong Wang, Di Huang, Chengyue Wu, Xihui Liu

NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction

Haofan Lu, Christopher Vattheuer, Baharan Mirzasoleiman, Omid Abari

CauDiTS: Causal Disentangled Domain Adaptation of Multivariate Time Series

Junxin Lu, Shiliang Sun

Rethinking Transformers in Solving POMDPs

Chenhao Lu, Ruizhe Shi, Yuyao Liu, Kaizhe Hu, Simon Shaolei Du

EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time

Shengyao Lu, Bang Liu, Keith G Mills, Jiao He, Di Niu

Open-Domain Text Evaluation via Contrastive Distribution Methods

Sidi Lu, Hongyi Liu, Asli Celikyilmaz, Tianlu Wang, Nanyun Peng

WebLINX: Real-World Website Navigation with Multi-Turn Dialogue

Xing Han Lu, Zdeněk Kasner, Siva Reddy

CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables

Jiecheng Lu, Xu Han, Yan Sun, Shihao Yang

Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training

Lin Lu, Chenxi Dai, Wangcheng Tao, Binhang Yuan, Yanan Sun

HumanTOMATO: Text-aligned Whole-body Motion Generation

Shunlin Lu, Ling-Hao Chen, Ailing Zeng, Jing Lin, Ruimao Zhang

Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models

Zhihe Lu, Jiawang Bai, Xin Li, Zeyu Xiao, Xinchao Wang

How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization

Andrew Lowy, Jonathan Ullman, Stephen Wright

Optimal Differentially Private Model Training with Public Data

Andrew Lowy, Zeman Li, Tianjian Huang, Meisam Razaviyayn

Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution

Aaron Lou, Chenlin Meng, Stefano Ermon

Non-Vacuous Generalization Bounds for Large Language Models

Sanae Lotfi, Marc Anton Finzi, Yilun Kuang, Tim G. J. Rudner, Micah Goldblum

Attention Meets Post-hoc Interpretability: A Mathematical Perspective

Gianluigi Lopardo, Frederic Precioso, Damien Garreau

Large Scale Dataset Distillation with Domain Shift

Noel Loo, Alaa Maalouf, Ramin Hasani, Mathias Lechner, Alexander Amini

Latent Noise Segmentation: How Neural Noise Leads to the Emergence of Segmentation and Grouping

Ben Lonnqvist, Zhengqing Wu, Michael Herzog

Position: Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?

Shayne Longpre, Robert Mahari, Naana Obeng-Marnu, William Brannon, Tobin South

Position: A Safe Harbor for AI Evaluation and Red Teaming

Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani

Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks

Yunfei Long, Zilin Tian, Liguo Zhang, Huosheng Xu

Position: The Causal Revolution Needs Scientific Pragmatism

Joshua R. Loftus

Restoring balance: principled under/oversampling of data for optimal classification

Emanuele Loffredo, Mauro Pastore, Simona Cocco, Remi Monasson

Coarse-To-Fine Tensor Trains for Compact Visual Representations

Sebastian Bugge Loeschcke, Dan Wang, Christian Munklinde Leth-Espensen, Serge Belongie, Michael Kastoryano

A Tensor Decomposition Perspective on Second-order RNNs

Maude Lizaire, Michael Rizvi-Martel, Marawan Gamal, Guillaume Rabusseau

Neural Operators with Localized Integral and Differential Kernels

Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli

Pairwise Alignment Improves Graph Domain Adaptation

Shikun Liu, Deyu Zou, Han Zhao, Pan Li

FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees

Jiahao Liu, Yipeng Zhou, Di Wu, Miao Hu, Mohsen Guizani

On the Last-Iterate Convergence of Shuffling Gradient Methods

Zijian Liu, Zhengyuan Zhou

Reducing Item Discrepancy via Differentially Private Robust Embedding Alignment for Privacy-Preserving Cross Domain Recommendation

Weiming Liu, Xiaolin Zheng, Chaochao Chen, Jiahe Xu, Xinting Liao

MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

Zechun Liu, Changsheng Zhao, Forrest Iandola, Chen Lai, Yuandong Tian

DFD: Distilling the Feature Disparity Differently for Detectors

Kang Liu, Yingyi Zhang, Jingyun Zhang, Jinmin Li, Jun Wang

SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models

Dongyang Liu, Renrui Zhang, Longtian Qiu, Siyuan Huang, Weifeng Lin

Timer: Generative Pre-trained Transformers Are Large Time Series Models

Yong Liu, Haoran Zhang, Chenyu Li, Xiangdong Huang, Jianmin Wang

Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design

Shuze Liu, Shangtong Zhang

KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache

Zirui Liu, Jiayi Yuan, Hongye Jin, Shaochen Zhong, Zhaozhuo Xu