Most Cited ICML "real datasets" Papers

Enhancing Storage and Computational Efficiency in Federated Multimodal Learning for Large-Scale Models

Zixin Zhang, Fan Qi, Changsheng Xu

Online Resource Allocation with Non-Stationary Customers

Xiaoyue Zhang, Hanzhang Qin, Mabel Chou

Optimal Fair Learning Robust to Adversarial Distribution Shift

Sushant Agarwal, Amit Jayant Deshpande, Rajmohan Rajaraman et al.

Online Matching with Stochastic Rewards: Provable Better Bound via Adversarial Reinforcement Learning

Qiankun Zhang, Aocheng Shen, Boyu Zhang et al.

Switchable Decision: Dynamic Neural Generation Networks

Shujian Zhang, Korawat Tanwisuth, Chengyue Gong et al.

GroupCover: A Secure, Efficient and Scalable Inference Framework for On-device Model Protection based on TEEs

Zheng Zhang, Na Wang, Ziqi Zhang et al.

Mind the Gap: A Practical Attack on GGUF Quantization

Kazuki Egashira, Robin Staab, Mark Vero et al.

Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting

Chen Huang, Skyler Seto, Hadi Pouransari et al.

Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective

Yulong Zhang, Yuan Yao, Shuhao Chen et al.

Optimizing Test-Time Compute via Meta Reinforcement Finetuning

Yuxiao Qu, Matthew Yang, Amrith Setlur et al.

Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets

Magzhan Gabidolla, Arman Zharmagambetov, Miguel Carreira-Perpinan

Distributionally Robust Data Valuation

Xiaoqiang Lin, Xinyi Xu, Zhaoxuan Wu et al.

Understanding the difficulties of posterior predictive estimation

Abhinav Agrawal, Justin Domke

Efficient Denoising Diffusion via Probabilistic Masking

Weizhong Zhang, Zhiwei Zhang, Renjie Pi et al.

ARS: Adaptive Reward Scaling for Multi-Task Reinforcement Learning

MYUNG-SIK CHO, Jong Eui Park, Jeonghye Kim et al.

Graph Adaptive Autoregressive Moving Average Models

Moshe Eliasof, Alessio Gravina, Andrea Ceni et al.

Probably Approximately Global Robustness Certification

Peter Blohm, Patrick Indri, Thomas Gärtner et al.

Can DBNNs Robust to Environmental Noise for Resource-constrained Scenarios?

Wendong Zheng, Junyang Chen, Husheng Guo et al.

Neural Jump-Diffusion Temporal Point Processes

Shuai Zhang, Chuan Zhou, Yang Liu et al.

Efficient Noise Calculation in Deep Learning-based MRI Reconstructions

Onat Dalmaz, Arjun Desai, Reinhard Heckel et al.

Accelerating Iterative Retrieval-augmented Language Model Serving with Speculation

Zhihao Zhang, Alan Zhu, Lijie Yang et al.

A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering

Lucas Fabian Naumann, Jannik Irmai, Bjoern Andres

Absolute Policy Optimization: Enhancing Lower Probability Bound of Performance with High Confidence

Weiye Zhao, Feihan Li, Yifan Sun et al.

Efficient Core-set Selection for Deep Learning Through Squared Loss Minimization

Jianting Chen

Rethinking Adversarial Robustness in the Context of the Right to be Forgotten

Chenxu Zhao, Wei Qian, Yangyi Li et al.

FedSSI: Rehearsal-Free Continual Federated Learning with Synergistic Synaptic Intelligence

Yichen Li, Yuying Wang, Haozhao Wang et al.

Point Cloud Dataset Distillation

Deyu Bo, Xinchao Wang

Unsupervised Representation Learning of Brain Activity via Bridging Voxel Activity and Functional Connectivity

Ali Behrouz, Parsa Delavari, Farnoosh Hashemi

Double-Step Alternating Extragradient with Increasing Timescale Separation for Finding Local Minimax Points: Provable Improvements

Kyuwon Kim, Donghwan Kim

TabSDS: a Lightweight, Fully Non-Parametric, and Model Free Approach for Generating Synthetic Tabular Data

Elias Chaibub Neto

Multidimensional Adaptive Coefficient for Inference Trajectory Optimization in Flow and Diffusion

Dohoon Lee, Jaehyun Park, Hyunwoo Kim et al.

Exploiting Negative Samples: A Catalyst for Cohort Discovery in Healthcare Analytics

Kaiping Zheng, Horng-Ruey Chua, Melanie Herschel et al.

Learning Monotonic Probabilities with a Generative Cost Model

Yongxiang Tang, Yanhua Cheng, Xiaocheng Liu et al.

DiffusionVLA: Scaling Robot Foundation Models via Unified Diffusion and Autoregression

Junjie Wen, Yichen Zhu, Minjie Zhu et al.

LLM-Assisted Semantically Diverse Teammate Generation for Efficient Multi-agent Coordination

Lihe Li, lei yuan, Pengsen Liu et al.

Batch List-Decodable Linear Regression via Higher Moments

Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.

Latent Variable Causal Discovery under Selection Bias

Haoyue Dai, Yiwen Qiu, Ignavier Ng et al.

ERQ: Error Reduction for Post-Training Quantization of Vision Transformers

Yunshan Zhong, Jiawei Hu, You Huang et al.

LEVIS: Large Exact Verifiable Input Spaces for Neural Networks

Mohamad Chehade, Wenting Li, Brian Bell et al.

GNNs Also Deserve Editing, and They Need It More Than Once

Shaochen (Henry) Zhong, Duy Le, Zirui Liu et al.

Causal-IQA: Towards the Generalization of Image Quality Assessment Based on Causal Inference

Yan Zhong, Xingyu Wu, Li Zhang et al.

On the Emergence of Cross-Task Linearity in Pretraining-Finetuning Paradigm

Zhanpeng Zhou, Zijun Chen, Yilan Chen et al.

Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations

Zhengming Chen, Yewei Xia, Feng Xie et al.

Online Learning in the Random-Order Model

Martino Bernasconi, Andrea Celli, Riccardo Colini Baldeschi et al.

Sequential Kernel Goodness-of-fit Testing

Zhengyu Zhou, Weiwei Liu

Private Model Personalization Revisited

Conor Snedeker, Xinyu Zhou, Raef Bassily

CurBench: Curriculum Learning Benchmark

Yuwei Zhou, Zirui Pan, Xin Wang et al.

Improving Zero-Shot Adversarial Robustness in Vision-Language Models by Closed-form Alignment of Adversarial Path Simplices

Junhao Dong, Piotr Koniusz, Yifei Zhang et al.

MVA: Linear Attention with High-order Query-Keys Integration and Multi-level Vocabulary Decomposition

ning wang, Zekun Li, Tongxin Bai et al.

Phase and Amplitude-aware Prompting for Enhancing Adversarial Robustness

Yibo Xu, Dawei Zhou, Decheng Liu et al.

Iterative Search Attribution for Deep Neural Networks

Zhiyu Zhu, Huaming Chen, Xinyi Wang et al.

Towards Escaping from Class Dependency Modeling for Multi-Dimensional Classification

Teng Huang, Bin-Bin Jia, Min-Ling Zhang

ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation

Tianci Bu, Le Zhou, Wenchuan Yang et al.

Learning Initial Basis Selection for Linear Programming via Duality-Inspired Tripartite Graph Representation and Comprehensive Supervision

Anqi Lu, Junchi Yan

Feature Shift Localization Network

Míriam Barrabés, Daniel Mas Montserrat, Kapal Dev et al.

Antibody Design Using a Score-based Diffusion Model Guided by Evolutionary, Physical and Geometric Constraints

Tian Zhu, Milong Ren, Haicang Zhang

Non-Asymptotic and Non-Lipschitzian Bounds on Optimal Values in Stochastic Optimization Under Heavy Tails

Jindong Tong, Hongcheng Liu, Johannes Royset

BAME: Block-Aware Mask Evolution for Efficient N:M Sparse Training

Chenyi yang, Wenjie Nie, Yuxin Zhang et al.

DeepLayout: Learning Neural Representations of Circuit Placement Layout

Yuxiang Zhao, zhuomin chai, Xun Jiang et al.

Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration

Zhengyang Zhuge, Peisong Wang, Xingting Yao et al.

Viewing Transformers Through the Lens of Long Convolutions Layers

Itamar Zimerman, Lior Wolf

Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity

Alessandro Montenegro, Marco Mussi, Matteo Papini et al.

BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization

Lancheng Zou, Wenqian Zhao, Shuo Yin et al.

Improving Equivariant Graph Neural Networks on Large Geometric Graphs via Virtual Nodes Learning

Yuelin Zhang, Jiacheng Cen, Jiaqi Han et al.

Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network

Jijia Liu, Feng Gao, Qingmin Liao et al.

Amend to Alignment: Decoupled Prompt Tuning for Mitigating Spurious Correlation in Vision-Language Models

Jie ZHANG, Xiaosong Ma, Song Guo et al.

Fast Tensor Completion via Approximate Richardson Iteration

Mehrdad Ghadiri, Matthew Fahrbach, Yunbum Kook et al.

Position: Is machine learning good or bad for the natural sciences?

David W. Hogg, Soledad Villar

Multi-class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data

Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini

Quadruple Attention in Many-body Systems for Accurate Molecular Property Predictions

Jiahua Rao, Dahao Xu, Wentao Wei et al.

Safe-EF: Error Feedback for Non-smooth Constrained Optimization

Rustem Islamov, Yarden As, Ilyas Fatkhullin

Scaling Beyond the GPU Memory Limit for Large Mixture-of-Experts Model Training

Yechan Kim, Hwijoon Lim, Dongsu Han

Adaptive Flow Matching for Resolving Small-Scale Physics

Stathi Fotiadis, Noah Brenowitz, Tomas Geffner et al.

EcoMapper: Generative Modeling for Climate-Aware Satellite Imagery

Muhammed Göktepe, Amir Hossein Shamseddin, Erencan Uysal et al.

Equivalence is All: A Unified View for Self-supervised Graph Learning

Yejiang Wang, Yuhai Zhao, Zhengkui Wang et al.

Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models

Mehmet Yiğit Balık, Maksim Sinelnikov, Priscilla Ong et al.

Differentially Private Sum-Product Networks

Xenia Heilmann, Mattia Cerrato, Ernst Althaus

ERICT: Enhancing Robustness by Identifying Concept Tokens in Zero-Shot Vision Language Models

Xinpeng Dong, Min Zhang, Didi Zhu et al.

MARGE: Improving Math Reasoning with Guided Exploration

Jingyue Gao, Runji Lin, Keming Lu et al.

Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements

Naman Agarwal, Satyen Kale, Karan Singh et al.

Physics Aware Neural Networks for Unsupervised Binding Energy Prediction

Ke Liu, Hao Chen, Chunhua Shen

Don't Restart, Just Reuse: Reoptimizing MILPs with Dynamic Parameters

Sijia Zhang, Shuli Zeng, Shaoang Li et al.

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

Youngsoo Jang, Geon-Hyeong Kim, Byoungjip Kim et al.

You Get What You Give: Reciprocally Fair Federated Learning

Aniket Murhekar, Jiaxin Song, Parnian Shahkar et al.

Disentangled Graph Spectral Domain Adaptation

Liang Yang, Xin Chen, Jiaming Zhuo et al.

In-Context Learning as Conditioned Associative Memory Retrieval

Weimin Wu, Teng-Yun Hsiao, Jerry Yao-Chieh Hu et al.

Reinforcement Learning Control of a Physical Robot Device for Assisted Human Walking without a Simulator

junmin zhong, Emiliano Quinones Yumbla, Seyed Yousef Soltanian et al.

Disentangled Continual Graph Neural Architecture Search with Invariant Modular Supernet

Zeyang Zhang, Xin Wang, Yijian Qin et al.

Disentangled Graph Self-supervised Learning for Out-of-Distribution Generalization

Haoyang Li, Xin Wang, Zeyang Zhang et al.

Knowledge-aware Reinforced Language Models for Protein Directed Evolution

Yuhao Wang, Qiang Zhang, Ming Qin et al.

Janus: Dual-Server Multi-Round Secure Aggregation with Verifiability for Federated Learning

Lang Pu, Jingjing Gu, Chao Lin et al.

DNCs Require More Planning Steps

Yara Shamshoum, Nitzan Hodos, Yuval Sieradzki et al.

I/O Complexity of Attention, or How Optimal is FlashAttention?

Barna Saha, Christopher Ye

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

Shayne Longpre, Robert Mahari, Naana Obeng-Marnu et al.

USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval

Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer et al.

Risk-Sensitive Theory of Mind: Coordinating with Agents of Unknown Bias using Cumulative Prospect Theory

Mason O. Smith, Wenlong Zhang

Federated Incomplete Multi-view Clustering with Globally Fused Graph Guidance

Guoqing Chao, Zhenghao Zhang, Lei Meng et al.

A Theoretical Analysis of Backdoor Poisoning Attacks in Convolutional Neural Networks

Boqi Li, Weiwei Liu

MoE-SVD: Structured Mixture-of-Experts LLMs Compression via Singular Value Decomposition

Wei Li, Lujun Li, Hao Gu et al.

Lightweight-Mark: Rethinking Deep Learning-Based Watermarking

Yupeng Qiu, Han Fang, Ee-Chien Chang

Splitting & Integrating: Out-of-Distribution Detection via Adversarial Gradient Attribution

Jiayu Zhang, Xinyi Wang, Zhibo Jin et al.

SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning

Yong Liu, Di Fu, Shenggan Cheng et al.

Online Differentially Private Conformal Prediction for Uncertainty Quantification

Language Models as Implicit Tree Search

Ziliang Chen, Zhao-Rong Lai, Yufeng Yang et al.

Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning

Bowen Zheng, Da-Wei Zhou, Han-Jia Ye et al.

Enforcing Constraints in RNA Secondary Structure Predictions: A Post-Processing Framework Based on the Assignment Problem

Geewon Suh, Gyeongjo Hwang, SeokjunKang et al.

Reshape and Adapt for Output Quantization (RAOQ): Quantization-aware Training for In-memory Computing Systems

Bonan Zhang, Chia-Yu Chen, Naveen Verma

Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptions

Le Tuyet Nhi PHAM, Dario Shariatian, Antonio Ocello et al.

Runtime Analysis of Evolutionary NAS for Multiclass Classification

Zeqiong Lv, Chao Qian, Yun Liu et al.

Be Confident: Uncovering Overfitting in MLLM Multi-Task Tuning

Wenke Huang, Jian Liang, Guancheng Wan et al.

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

Shomik Jain, Kathleen A. Creel, Ashia Wilson

Algorithmic Recourse for Long-Term Improvement

Kentaro Kanamori, Ken Kobayashi, Satoshi Hara et al.

Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization

Yirui Liu, Xinghao Qiao, Yulong Pei et al.

What Do Learning Dynamics Reveal About Generalization in LLM Mathematical Reasoning?

Katie Kang, Amrith Setlur, Dibya Ghosh et al.

PerceptAnon: Exploring the Human Perception of Image Anonymization Beyond Pseudonymization for GDPR

Kartik Patwari, Chen-Nee Chuah, Lingjuan Lyu et al.

Do Topological Characteristics Help in Knowledge Distillation?

Jungeun Kim, Junwon You, Dongjin Lee et al.

Partially Stochastic Infinitely Deep Bayesian Neural Networks

Sergio Calvo Ordoñez, Matthieu Meunier, Francesco Piatti et al.

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

Mohannad Elhamod, Anuj Karpatne

EvFocus: Learning to Reconstruct Sharp Images from Out-of-Focus Event Streams

Lin Zhu, Xiantao Ma, Xiao Wang et al.

Efficient and Separate Authentication Image Steganography Network

Junchao Zhou, Yao Lu, Jie Wen et al.

Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models

Daiki Chijiwa, Taku Hasegawa, Kyosuke Nishida et al.

Improving Soft Unification with Knowledge Graph Embedding Methods

Xuanming Cui, Chionh Peng, Adriel Kuek et al.

How Does Goal Relabeling Improve Sample Efficiency?

Sirui Zheng, Chenjia Bai, Zhuoran Yang et al.

Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling

Zehao Dou, Minshuo Chen, Mengdi Wang et al.

Be a Goldfish: Forgetting Bad Conditioning in Sparse Linear Regression via Variational Autoencoders

Kuheli Pratihar, Debdeep Mukhopadhyay

Momentum-Driven Adaptivity: Towards Tuning-Free Asynchronous Federated Learning

Wenjing Yan, Xiangyu Zhong, Xiaolu Wang et al.

Analysis for Abductive Learning and Neural-Symbolic Reasoning Shortcuts

Xiao-Wen Yang, Wen-Da Wei, Jie-Jing Shao et al.

Bootstrapping Self-Improvement of Language Model Programs for Zero-Shot Schema Matching

Nabeel Seedat, Mihaela van der Schaar

To Each Metric Its Decoding: Post-Hoc Optimal Decision Rules of Probabilistic Hierarchical Classifiers

Roman Plaud, Alexandre Perez-Lebel, Matthieu Labeau et al.

CERTAIN: Context Uncertainty-aware One-Shot Adaptation for Context-based Offline Meta Reinforcement Learning

Hongtu Zhou, Ruiling Yang, Yakun Zhu et al.

MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning

Peter Eckmann, Dongxia Wu, Germano Heinzelmann et al.

Conservative Offline Goal-Conditioned Implicit V-Learning

Ke Kaiqiang, qian lin, Zongkai Liu et al.

SkipGPT: Each Token is One of a Kind

Anhao Zhao, Fanghua Ye, Yingqi Fan et al.

Online Episodic Convex Reinforcement Learning

Bianca Marin Moreno, Khaled Eldowa, Pierre Gaillard et al.

NeuralIndicator: Implicit Surface Reconstruction from Neural Indicator Priors

Shi-Sheng Huang, Guo Chen, Li-heng Chen et al.

Scalable Approximation Algorithms for $p$-Wasserstein Distance and Its Variants

Nathaniel Lahn, Sharath Raghvendra, Emma Saarinen et al.

Discovering Symbolic Cognitive Models from Human and Animal Behavior

Pablo Samuel Castro, Nenad Tomasev, Ankit Anand et al.

Implicit Language Models are RNNs: Balancing Parallelization and Expressivity

Mark Schoene, Babak Rahmani, Heiner Kremer et al.

WeGeFT: Weight‑Generative Fine‑Tuning for Multi‑Faceted Efficient Adaptation of Large Models

Chinmay Savadikar, Xi Song, Tianfu Wu

DFD: Distilling the Feature Disparity Differently for Detectors

Kang Liu, Yingyi Zhang, Jingyun Zhang et al.

In-Context Unlearning: Language Models as Few-Shot Unlearners

Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju

General agents need world models

Jonathan Richens, Tom Everitt, David Abel

Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs

Stelios Triantafyllou, Aleksa Sukovic, Debmalya Mandal et al.

KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions

Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki et al.

Physics-Informed Weakly Supervised Learning For Interatomic Potentials

Makoto Takamoto, Viktor Zaverkin, Mathias Niepert

Modularized Self-Reflected Video Reasoner for Multimodal LLM with Application to Video Question Answering

Zihan Song, Xin Wang, Zi Qian et al.

How Distributed Collaboration Influences the Diffusion Model Training? A Theoretical Perspective

Jing Qiao, Yu Liu, YUAN YUAN et al.

FedClean: A General Robust Label Noise Correction for Federated Learning

Xiaoqian Jiang, Jing Zhang

Contextual Optimization Under Model Misspecification: A Tractable and Generalizable Approach

Omar Bennouna, Jiawei Zhang, Saurabh Amin et al.

On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions

Denys Pushkin, Raphaël Berthier, Emmanuel Abbe

The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability

Jiachen Hu, Rui Ai, Han Zhong et al.

Deep Neural Cellular Potts Models

Koen Minartz, Tim d'Hondt, Leon Hillmann et al.

Energy-based Backdoor Defense without Task-Specific Samples and Model Retraining

Yudong Gao, Honglong Chen, Peng Sun et al.

An Effective and Secure Federated Multi-View Clustering Method with Information-Theoretic Perspective

Xinyue Chen, Jinfeng Peng, Yuhao Li et al.

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

Florian Dorner, Moritz Hardt

Square$\chi$PO: Differentially Private and Robust $\chi^2$-Preference Optimization in Offline Direct Alignment

Xingyu Zhou, Yulian Wu, Wenqian Weng et al.

Causally Motivated Personalized Federated Invariant Learning with Shortcut-Averse Information-Theoretic Regularization

Xueyang Tang, Song Guo, Jingcai Guo et al.

Multi-Armed Bandits with Interference: Bridging Causal Inference and Adversarial Bandits

Su Jia, Peter Frazier, Nathan Kallus

Global Convergence and Rich Feature Learning in $L$-Layer Infinite-Width Neural Networks under $\mu$ Parametrization

Zixiang Chen, Greg Yang, Qingyue Zhao et al.

Delay-DSGN: A Dynamic Spiking Graph Neural Network with Delay Mechanisms for Evolving Graph

Zhiqiang Wang, Jianghao Wen, Jianqing Liang

Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms

Sho Takemori, Yuhei Umeda, Aditya Gopalan

On the Statistical Mechanisms of Distributional Compositional Generalization

Jingwen Fu, Nanning Zheng

Offline Model-based Optimization for Real-World Molecular Discovery

Dong-Hee Shin, Young-Han Son, Hyun Jung Lee et al.

Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving

Sohei Arisaka, Qianxiao Li

MATS: An Audio Language Model under Text-only Supervision

Wen Wang, Ruibing Hou, Hong Chang et al.

Censor Dependent Variational Inference

Chuanhui Liu, Xiao Wang

Textural or Textual: How Vision-Language Models Read Text in Images

Hanzhang Wang, Qingyuan Ma

Reducing Confounding Bias without Data Splitting for Causal Inference via Optimal Transport

Yuguang Yan, Zongyu Li, Haolin Yang et al.

CodeIO: Condensing Reasoning Patterns via Code Input-Output Prediction

Junlong Li, Daya Guo, Dejian Yang et al.

BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach

Haozhao Wang, Shengyu Wang, Jiaming Li et al.

Sequential Asynchronous Action Coordination in Multi-Agent Systems: A Stackelberg Decision Transformer Approach

Bin Zhang, Hangyu Mao, Lijuan Li et al.

MathConstruct: Challenging LLM Reasoning with Constructive Proofs

Mislav Balunovic, Jasper Dekoninck, Nikola Jovanović et al.

HEAP: Hyper Extended A-PDHG Operator for Constrained High-dim PDEs

Mingquan Feng, Weixin Liao, Yixin Huang et al.

The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright BreachesWithout Adjusting Finetuning Pipeline

Haonan Wang, Qianli Shen, Yao Tong et al.

Dynamic Spectral Clustering with Provable Approximation Guarantee

Steinar Laenen, He Sun

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

Haonan Huang, Guoxu Zhou, Yanghang Zheng et al.

Concept Reachability in Diffusion Models: Beyond Dataset Constraints

Marta Aparicio Rodriguez, Xenia Miscouridou, Anastasia Borovykh

Learning to Explore in POMDPs with Informational Rewards

Annie Xie, Logan M. Bhamidipaty, Evan Liu et al.

Computing Voting Rules with Improvement Feedback

Evi Micha, Vasilis Varsamis

Circumventing Backdoor Space via Weight Symmetry

Jie Peng, Hongwei Yang, Jing Zhao et al.

Speech Self-Supervised Learning Using Diffusion Model Synthetic Data

Heting Gao, Kaizhi Qian, Junrui Ni et al.

Structure-Guided Large Language Models for Text-to-SQL Generation

Qinggang Zhang, Hao Chen, Junnan Dong et al.

Learning to Steer Learners in Games

Yizhou Zhang, Yian Ma, Eric Mazumdar

GS-Bias: Global-Spatial Bias Learner for Single-Image Test-Time Adaptation of Vision-Language Models

Zhaohong Huang, Yuxin Zhang, JingJing Xie et al.

Enhancing Ligand Validity and Affinity in Structure-Based Drug Design with Multi-Reward Optimization

Seungbeom Lee, Munsun Jo, Jungseul Ok et al.

Flow Matching for Denoised Social Recommendation

Yinxuan Huang, KE LIANG, Zhuofan Dong et al.

Information-Directed Pessimism for Offline Reinforcement Learning

Alec Koppel, Sujay Bhatt, Jiacheng Guo et al.

Partial Optimality in the Linear Ordering Problem

David Stein, Bjoern Andres

Differentially Private Domain Adaptation with Theoretical Guarantees

Raef Bassily, Corinna Cortes, Anqi Mao et al.

Learning from Sample Stability for Deep Clustering

Zhixin Li, Yuheng Jia, Hui LIU et al.

Slimming the Fat-Tail: Morphing-Flow for Adaptive Time Series Modeling

Tianyu Liu, kai sun, Fuchun Sun et al.

PiD: Generalized AI-Generated Images Detection with Pixelwise Decomposition Residuals

Xinghe Fu, Zhiyuan Yan, Zheng Yang et al.

Box Facets and Cut Facets of Lifted Multicut Polytopes

Lucas Fabian Naumann, Jannik Irmai, Shengxian Zhao et al.

Improving Computational Complexity in Statistical Models with Local Curvature Information

Pedram Akbarian, Tongzheng Ren, Jiacheng Zhuo et al.

CoastalBench: A Decade-Long High-Resolution Dataset to Emulate Complex Coastal Processes

Zelin Xu, Yupu Zhang, Tingsong Xiao et al.

Generalization Analysis of Deep Non-linear Matrix Completion

Antoine Ledent, Rodrigo Alves

Redundancy Undermines the Trustworthiness of Self-Interpretable GNNs

Wenxin Tai, Ting Zhong, Goce Trajcevski et al.

R2E: Turning any Github Repository into a Programming Agent Environment

Naman Jain, Manish Shetty Molahalli, Tianjun Zhang et al.

Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning

Yun-Hsuan Lien, Ping-Chun Hsieh, Tzu-Mao Li et al.

CFPT: Empowering Time Series Forecasting through Cross-Frequency Interaction and Periodic-Aware Timestamp Modeling

Feifei Kou, Jiahao Wang, Lei Shi et al.