ICML 2024

2,610 papers

Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations

Yanda Chen, Ruiqi Zhong, Narutatsu Ri, Chen Zhao, He He

Enhancing Implicit Shape Generators Using Topological Regularizations

Liyan Chen, YAN ZHENG, Yang Li, Lohit Anirudh Jagarapu, Haoxiang Li

Compact Optimality Verification for Optimization Proxies

Wenbo Chen, Haoruo Zhao, Mathieu Tanneau, Pascal Van Hentenryck

HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding

Zhaorun Chen, Zhuokai Zhao, Hongyin Luo, Huaxiu Yao, Bo Li

LLaGA: Large Language and Graph Assistant

Runjin Chen, Tong Zhao, Ajay Kumar Jaiswal, Neil Shah, Zhangyang Wang

MoE-RBench: Towards Building Reliable Language Models with Sparse Mixture-of-Experts

Guanjie Chen, Xinyu Zhao, Tianlong Chen, Yu Cheng

Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation

Yu Chen, Xiangcheng Zhang, Siwei Wang, Longbo Huang

Diffusive Gibbs Sampling

Wenlin Chen, Mingtian Zhang, Brooks Paige, José Miguel Hernández-Lobato, David Barber

Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks

Zhuomin Chen, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian

One for All: A Universal Generator for Concept Unlearnability via Multi-Modal Alignment

Chaochao Chen, Jiaming Zhang, Yuyuan Li, Zhongxuan Han

Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness

Honghao Chen, Yurong Zhang, Xiaokun Feng, Xiangxiang Chu, Kaiqi Huang

FedMBridge: Bridgeable Multimodal Federated Learning

Jiayi Chen, Aidong Zhang

$\rm E(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning

Dingyang Chen, Qi Zhang

DRCT: Diffusion Reconstruction Contrastive Training towards Universal Detection of Diffusion Generated Images

Baoying Chen, Jishen Zeng, Jianquan Yang, Rui Yang

Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration

Xiong-Hui Chen, Junyin Ye, Hang Zhao, Yi-Chen Li, Xu-Hui Liu

Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting

Anthony Chen, Huanrui Yang, Yulu Gan, Denis A Gudovskiy, Zhen Dong

In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation

shiqi chen, Miao Xiong, Junteng Liu, Zhengxuan Wu, Teng Xiao

Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning

Junfeng Chen, Kailiang Wu

AutoOS: Make Your OS More Powerful by Exploiting Large Language Models

Huilai Chen, Yuanbo Wen, Limin Cheng, Shouxu Kuang, Yumeng Liu

Diffusion Model-Augmented Behavioral Cloning

Shang-Fu Chen, Hsiang-Chun Wang, Ming-Hao Hsu, Chun-Mao Lai, Shao-Hua Sun

A General Framework for Learning from Weak Supervision

Hao Chen, Jindong Wang, Lei Feng, Xiang Li, Yidong Wang

Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments

Runfa Chen, Ling Wang, Yu Du, Tianrui Xue, Fuchun Sun

Locally Differentially Private Decentralized Stochastic Bilevel Optimization with Guaranteed Convergence Accuracy

Ziqin Chen, Yongqiang Wang

SelfIE: Self-Interpretation of Large Language Model Embeddings

Haozhe Chen, Carl Vondrick, Chengzhi Mao

Recovering Labels from Local Updates in Federated Learning

Huancheng Chen, Haris Vikalo

Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes

Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan Suykens

Performative Prediction with Bandit Feedback: Learning through Reparameterization

Yatong Chen, Wei Tang, Chien-Ju Ho, Yang Liu

Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts

Shengzhuang Chen, Jihoon Tack, Yunqiao Yang, Yee Whye Teh, Jonathan Richard Schwarz

GRATH: Gradual Self-Truthifying for Large Language Models

Weixin Chen, Dawn Song, Bo Li

CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process

Guangyi Chen, Yifan Shen, Zhenhao Chen, Xiangchen Song, Yuewen Sun

MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models

Justin Chen, Swarnadeep Saha, Elias Stengel-Eskin, Mohit Bansal

AegisFL: Efficient and Flexible Privacy-Preserving Byzantine-Robust Cross-silo Federated Learning

Dong Chen, Hongyuan Qu, Guangwu Xu

TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning

Xiwen Chen, Peijie Qiu, Wenhui Zhu, Huayu Li, Hao Wang

EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism

Yanxi Chen, Xuchen Pan, Yaliang Li, Bolin Ding, Jingren Zhou

TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision

Zhuo Chen, Jacob Mccarran, Esteban Vizcaino, Marin Soljacic, Di Luo

GeoMFormer: A General Architecture for Geometric Molecular Representation Learning

Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-yan Liu

DiJiang: Efficient Large Language Models through Compact Kernelization

Hanting Chen, Liu Zhicheng, Xutao Wang, Yuchuan Tian, Yunhe Wang

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization

Yihang Chen, Fanghui Liu, Taiji Suzuki, Volkan Cevher

Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank

Mouxiang Chen, Chenghao Liu, Zemin Liu, Zhuo Li, Jianling Sun

Toward Adaptive Reasoning in Large Language Models with Thought Rollback

Sijia Chen, Baochun Li

Efficient Pareto Manifold Learning with Low-Rank Structure

Weiyu Chen, James Kwok

Offline Transition Modeling via Contrastive Energy Learning

Ruifeng Chen, Chengxing Jia, Zefang Huang, Tian-Shuo Liu, Xu-Hui Liu

Improved Communication-Privacy Trade-offs in L_2 Mean Estimation under Streaming Differential Privacy

Wei-Ning Chen, Berivan Isik, Peter Kairouz, Albert No, Sewoong Oh

From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning

Wei Chen, Zhen Huang, Liang Xie, Binbin Lin, Houqiang Li

Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning

Yen-Ju Chen, Nai-Chieh Huang, Ching-pei Lee, Ping-Chun Hsieh

Accelerated Policy Gradient for s-rectangular Robust MDPs with Large State Spaces

Ziyi Chen, Heng Huang

Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers

Brian K Chen, Tianyang Hu, Hui Jin, Hwee Kuan Lee, Kenji Kawaguchi

Bagged Deep Image Prior for Recovering Images in the Presence of Speckle Noise

Xi Chen, Zhewen Hou, Christopher Metzler, Arian Maleki, Shirin Jalali

On Interpolating Experts and Multi-Armed Bandits

Houshuang Chen, Yuchen He, Chihao Zhang

CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding

Kaiyuan Chen, Xingzhuo Guo, Yu Zhang, Jianmin Wang, Mingsheng Long

Probabilistic Forecasting with Stochastic Interpolants and Föllmer Processes

Yifan Chen, Mark Goldstein, Mengjian Hua, Michael Samuel Albergo, Nicholas Matthew Boffi

Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components

Zhiliang Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low

Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective

Yang Chen, Cong Fang, Zhouchen Lin, Bing Liu

Robust Classification via a Single Diffusion Model

Huanran Chen, Yinpeng Dong, Zhengyi Wang, Xiao Yang, Chengqi Duan

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

Zixiang Chen, Yihe Deng, Huizhuo Yuan, Kaixuan Ji, Quanquan Gu

Premise Order Matters in Reasoning with Large Language Models

Xinyun Chen, Ryan Andrew Chi, Xuezhi Wang, Denny Zhou

MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark

Dongping Chen, Ruoxi Chen, Shilin Zhang, Yaochen Wang, Yinuo Liu

Policy-conditioned Environment Models are More Generalizable

Ruifeng Chen, Xiong-Hui Chen, Yihao Sun, Siyuan Xiao, Minhui Li

MaSS: Multi-attribute Selective Suppression for Utility-preserving Data Transformation from an Information-theoretic Perspective

Yizhuo Chen, Chun-Fu Chen, Hsiang Hsu, Shaohan Hu, Marco Pistoia

InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models

Lichang Chen, Jiuhai Chen, Tom Goldstein, Heng Huang, Tianyi Zhou

Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation

Xuexin Chen, Ruichu Cai, Zhengting Huang, Yuxuan Zhu, Julien Horwood

Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning

Weilin Chen, Ruichu Cai, Zeqin Yang, Jie Qiao, Yuguang Yan

How Interpretable Are Interpretable Graph Neural Networks?

Yongqiang Chen, Yatao Bian, Bo Han, James Cheng

PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer

Chang Chen, Junyeob Baek, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre

Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation

Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi

Performance Bounds for Active Binary Testing with Information Maximization

Aditya Chattopadhyay, Benjamin David Haeffele, René Vidal, Donald Geman

On the Role of Edge Dependency in Graph Generative Models

Sudhanshu Chanpuriya, Cameron N Musco, Konstantinos Sotiropoulos, Charalampos Tsourakakis

From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions

Trenton Chang, Jenna Wiens

MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion

Di Chang, Yichun Shi, Quankai Gao, Hongyi Xu, Jessica Fu

LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits

Chen-Chia Chang, Yikang Shen, Shaoze Fan, Jing Li, Shun Zhang

Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting

Serina Chang, Frederic Koehler, Zhaonan Qu, Jure Leskovec, Johan Ugander

Feature Importance Disparities for Data Bias Investigations

Peter W Chang, Leor Fishman, Seth Neel

Scribble-Supervised Semantic Segmentation with Prototype-based Feature Augmentation

Guiyang Chan, Pengcheng Zhang, Hai Dong, Shunhui Ji, Bainian Chen

Dense Reward for Free in Reinforcement Learning from Human Feedback

Alex James Chan, Hao Sun, Samuel Holt, Mihaela van der Schaar

MaxMin-RLHF: Alignment with Diverse Human Preferences

Souradip Chakraborty, Jiahao Qiu, Hui Yuan, Alec Koppel, Dinesh Manocha

Position: On the Possibilities of AI-Generated Text Detection

Souradip Chakraborty, Amrit Bedi, Sicheng Zhu, Bang An, Dinesh Manocha

Auditing Private Prediction

Karan Chadha, Matthew Jagielski, Nicolas Papernot, Christopher A. Choquette-Choo, Milad Nasr

Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning

Sungmin Cha, Kyunghyun Cho, Taesup Moon

Simple Ingredients for Offline Reinforcement Learning

Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier

Feasibility Consistent Representation Learning for Safe Reinforcement Learning

Zhepeng Cen, Yihang Yao, ZUXIN LIU, Ding Zhao

Using Left and Right Brains Together: Towards Vision and Language Planning

Jun CEN, Chenfei Wu, Xiao Liu, Shengming Yin, Yixuan Pei

Centralized Selection with Preferences in the Presence of Biases

L. Elisa Celis, Amit Kumar, Nisheeth K. Vishnoi, Andrew Xu

Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts

Onur Celik, Aleksandar Taranovic, Gerhard Neumann

On the Implicit Bias of Adam

Matias D. Cattaneo, Jason Matthew Klusowski, Boris Shigida

Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity

Marta Catalano, Hugo Lavenant

How Smooth Is Attention?

Valérie Castin, Pierre Ablin, Gabriel Peyré

Online Learning under Budget and ROI Constraints via Weak Adaptivity

Matteo Castiglioni, Andrea Celli, Christian Kroer

Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback

Asaf Cassel, Haipeng Luo, Aviv Rosenberg, Dmitry Sotnikov

AI Alignment with Changing and Influenceable Reward Functions

Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca Dragan

Stealing part of a production language model

Nicholas Carlini, Daniel Paleka, Krishnamurthy Dj Dvijotham, Thomas Steinke, Jonathan Hayase

Can a Few Decide for Many? The Metric Distortion of Sortition

Ioannis Caragiannis, Evi Micha, Jannik Peters

Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection

Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu

Predictive Dynamic Fusion

Bing Cao, Yinan Xia, Yi Ding, Changqing Zhang, Qinghua Hu

Limited Preference Aided Imitation Learning from Imperfect Demonstrations

Xingchen Cao, Fan-Ming Luo, Junyin Ye, Tian Xu, Zhilong Zhang

Successor Features for Efficient Multi-Subject Controlled Text Generation

Meng Cao, Mehdi Fatemi, Jackie CK Cheung, Samira Shabanian

Graph Positional and Structural Encoder

Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf

Mimicking Better by Matching the Approximate Action Distribution

Joao Candido Ramos, Lionel Blondé, Naoya Takeishi, Alexandros Kalousis

Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design

Andrew Campbell, Jason Yim, Regina Barzilay, Tom Rainforth, Tommi Jaakkola

Partially Stochastic Infinitely Deep Bayesian Neural Networks

Sergio Calvo Ordoñez, Matthieu Meunier, Francesco Piatti, Yuantao Shi

Human Alignment of Large Language Models through Online Preference Optimisation

Daniele Calandriello, Zhaohan Daniel Guo, Rémi Munos, Mark Rowland, Yunhao Tang