Yin, Ming

46 publications

AAAI 2025 K-Hop Hypergraph Neural Network: A Comprehensive Aggregation Approach Linhuang Xie, Shihao Gao, Jie Liu, Ming Yin, Taisong Jin

ICCV 2025 Keyframe-Oriented Vision Token Pruning: Enhancing Efficiency of Large Vision Language Models on Long-Form Video Processing Yudong Liu, Jingwei Sun, Yueqian Lin, Jianyi Zhang, Jingyang Zhang, Ming Yin, Qinsi Wang, Hai Li, Yiran Chen

ICLRW 2025 LoBAM: LoRA-Based Backdoor Attack on Model Merging Ming Yin, Jingyang Zhang, Jingwei Sun, Minghong Fang, Hai Helen Li, Yiran Chen

ICLRW 2025 MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities Against Hard Perturbations Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang

ICML 2025 MATH-Perturb: Benchmarking LLMs’ Math Reasoning Abilities Against Hard Perturbations Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang

L4DC 2025 Rates for Offline Reinforcement Learning with Adaptively Collected Data Sunil Madhow, Dan Qiao, Ming Yin, Yu-Xiang Wang

ICML 2025 Which Agent Causes Task Failures and When? on Automated Failure Attribution of LLM Multi-Agent Systems Shaokun Zhang, Ming Yin, Jieyu Zhang, Jiale Liu, Zhiguang Han, Jingyang Zhang, Beibin Li, Chi Wang, Huazheng Wang, Yiran Chen, Qingyun Wu

NeurIPS 2024 A Theoretical Perspective for Speculative Decoding Algorithm Ming Yin, Minshuo Chen, Kaixuan Huang, Mengdi Wang

ICMLW 2024 Accelerating Best-of-N via Speculative Rejection Ruiqi Zhang, Momin Haider, Ming Yin, Jiahao Qiu, Mengdi Wang, Peter Bartlett, Andrea Zanette

ICMLW 2024 Accelerating Best-of-N via Speculative Rejection Ruiqi Zhang, Momin Haider, Ming Yin, Jiahao Qiu, Mengdi Wang, Peter Bartlett, Andrea Zanette

ICMLW 2024 Accelerating Best-of-N via Speculative Rejection Ruiqi Zhang, Momin Haider, Ming Yin, Jiahao Qiu, Mengdi Wang, Peter Bartlett, Andrea Zanette

AAAI 2024 Decoding AI's Nudge: A Unified Framework to Predict Human Behavior in AI-Assisted Decision Making Zhuoyan Li, Zhuoran Lu, Ming Yin

IJCAI 2024 Designing Behavior-Aware AI to Improve the Human-AI Team Performance in AI-Assisted Decision Making Syed Hasan Amin Mahmood, Zhuoran Lu, Ming Yin

NeurIPS 2024 Fast Best-of-N Decoding via Speculative Rejection Hanshi Sun, Momin Haider, Ruiqi Zhang, Huitao Yang, Jiahao Qiu, Ming Yin, Mengdi Wang, Peter L. Bartlett, Andrea Zanette

ICML 2024 Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games Songtao Feng, Ming Yin, Yu-Xiang Wang, Jing Yang, Yingbin Liang

ICML 2024 Learning the Target Network in Function Space Kavosh Asadi, Yao Liu, Shoham Sabach, Ming Yin, Rasool Fakoor

CVPR 2024 MMMU: A Massive Multi-Discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, Cong Wei, Botao Yu, Ruibin Yuan, Renliang Sun, Ming Yin, Boyuan Zheng, Zhenzhu Yang, Yibo Liu, Wenhao Huang, Huan Sun, Yu Su, Wenhu Chen

NeurIPS 2024 NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation Momin Haider, Ming Yin, Menglei Zhang, Arpit Gupta, Jing Zhu, Yu-Xiang Wang

NeurIPS 2024 Offline Multitask Representation Learning for Reinforcement Learning Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup

NeurIPS 2024 Transfer Q-Star : Principled Decoding for LLM Alignment Souradip Chakraborty, Soumya Suvra Ghosal, Ming Yin, Dinesh Manocha, Mengdi Wang, Amrit Singh Bedi, Furong Huang

NeurIPS 2024 Utilizing Human Behavior Modeling to Manipulate Explanations in AI-Assisted Decision Making: The Good, the Bad, and the Scary Zhuoyan Li, Ming Yin

AAAI 2023 Modeling Human Trust and Reliance in AI-Assisted Decision Making: A Markovian Approach Zhuoyan Li, Zhuoran Lu, Ming Yin

UAI 2023 No-Regret Linear Bandits Beyond Realizability Chong Liu, Ming Yin, Yu-Xiang Wang

ICML 2023 Non-Stationary Reinforcement Learning Under General Function Approximation Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang

ICML 2023 Offline Reinforcement Learning with Closed-Form Policy Improvement Operators Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai, Yu-Xiang Wang, William Yang Wang

ICLR 2023 Offline Reinforcement Learning with Differentiable Function Approximation Is Provably Efficient Ming Yin, Mengdi Wang, Yu-Xiang Wang

AAAI 2023 On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora

NeurIPS 2023 Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yian Ma

IJCAI 2023 Strategic Adversarial Attacks in AI-Assisted Decision Making to Reduce Human Trust and Reliance Zhuoran Lu, Zhuoyan Li, Chun-Wei Chiang, Ming Yin

IJCAI 2023 The Effects of AI Biases and Explanations on Human Decision Fairness: A Case Study of Bidding in Rental Housing Markets Xinru Wang, Chen Liang, Ming Yin

ICMLW 2023 Why Quantization Improves Generalization: NTK of Binary Weight Neural Network Kaiqi Zhang, Ming Yin, Yu-Xiang Wang

ICLR 2022 Near-Optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang

NeurIPSW 2022 Offline Reinforcement Learning with Closed-Form Policy Improvement Operators Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai, Yu-Xiang Wang, William Yang Wang

UAI 2022 Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang

ICML 2022 Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost Dan Qiao, Ming Yin, Ming Min, Yu-Xiang Wang

AISTATS 2021 Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning Ming Yin, Yu Bai, Yu-Xiang Wang

IJCAI 2021 Accounting for Confirmation Bias in Crowdsourced Label Aggregation Meric Altug Gemalmaz, Ming Yin

IJCAI 2021 Exploring the Effects of Goal Setting When Training for Complex Crowdsourcing Tasks (Extended Abstract) Amy Rechkemmer, Ming Yin

NeurIPS 2021 Near-Optimal Offline Reinforcement Learning via Double Variance Reduction Ming Yin, Yu Bai, Yu-Xiang Wang

NeurIPS 2021 Optimal Uniform OPE and Model-Based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings Ming Yin, Yu-Xiang Wang

NeurIPS 2021 Towards Instance-Optimal Offline Reinforcement Learning with Pessimism Ming Yin, Yu-Xiang Wang

AISTATS 2020 Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning Ming Yin, Yu-Xiang Wang

AAAI 2020 Shared Generative Latent Representation Learning for Multi-View Clustering Ming Yin, Weitian Huang, Junbin Gao

CVPR 2016 Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds Ming Yin, Yi Guo, Junbin Gao, Zhaoshui He, Shengli Xie

IJCAI 2015 Bonus or Not? Learn to Reward in Crowdsourcing Ming Yin, Yiling Chen

AAAI 2013 The Effects of Performance-Contingent Financial Incentives in Online Labor Markets Ming Yin, Yiling Chen, Yuan Sun