| 2026 | AAAI | Align When They Want, Complement When They Need! Human-Centered Ensembles for Adaptive Human-AI Collaboration. | Syed Hasan Amin Mahmood, Ming Yin, Rajiv Khanna |
| 2026 | AAAI | NumCoKE: Ordinal-Aware Numerical Reasoning over Knowledge Graphs with Mixture-of-Experts and Contrastive Learning. | Ming Yin, Zongsheng Cao, Qiqing Xia, Chenyang Tu, Neng Gao |
| 2026 | AAAI | Assessing Automated Fact-Checking for Medical LLM Responses with Knowledge Graphs. | Shasha Zhou, Mingyu Huang, Jack Cole, Charles Britton, Ming Yin, Jan Wolber, Ke Li |
| 2026 | ACL | From Fallback to Frontline: When Can LLMs be Superior Annotators of Human Perspectives? | Hasan Amin, Harry Yizhou Tian, Xiaoni Duan, Chien-Ju Ho, Rajiv Khanna, Ming Yin |
| 2026 | CHI | Large Language Model (LLM)-driven Adversarial Social Influences in Online Information Spread: Risks and Interventions. | Zhuoran Lu, Gionnieve Lim, Ming Yin |
| 2026 | CHI | Understanding the Effects of AI-Assisted Critical Thinking on Human-AI Decision Making. | Harry Yizhou Tian, Hasan Amin, Ming Yin |
| 2026 | CHI | XAgen: An Explainability Tool for Identifying and Correcting Failures in Multi-Agent Workflows. | Xinru Wang, Ming Yin, Eunyee Koh, Mustafa Doga Dogan |
| 2025 | AAAI | K-hop Hypergraph Neural Network: A Comprehensive Aggregation Approach. | Linhuang Xie, Shihao Gao, Jie Liu, Ming Yin, Taisong Jin |
| 2025 | CHI | From Text to Trust: Empowering AI-assisted Decision Making with Adaptive LLM-powered Analysis. | Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, Ziang Xiao, Ming Yin |
| 2025 | CHI | Understanding the Effects of Large Language Model (LLM)-driven Adversarial Social Influences in Online Information Spread. | Zhuoran Lu, Gionnieve Lim, Ming Yin |
| 2025 | CHI | Understanding the Effects of AI-based Credibility Indicators When People Are Influenced By Both Peers and Experts. | Zhuoran Lu, Patrick Li, Weilong Wang, Ming Yin |
| 2025 | CHI | Towards Human-AI Deliberation: Design and Evaluation of LLM-Empowered Deliberative AI for AI-Assisted Decision-Making. | Shuai Ma, Qiaoyi Chen, Xinru Wang, Chengbo Zheng, Zhenhui Peng, Ming Yin, Xiaojuan Ma |
| 2025 | CSCW | Augmenting Collaborative Problem-Solving: Exploring the Design and Use of GenAI for Groupwork. | Janet G. Johnson, Steven R. Rick, Jens Emil Grnbk, Emily Wong, Ming Yin, Michael Nebeling, Mark Klein, Mark S. Ackerman, Thomas W. Malone |
| 2025 | ICCV | 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 |
| 2025 | ICML | 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 |
| 2025 | ICML | 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 |
| 2025 | KDD | On the Support Vector Effect in DNNs: Rethinking Data Selection and Attribution. | Syed Hasan Amin Mahmood, Ming Yin, Rajiv Khanna |
| 2025 | MICCAI | Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation. | Ming Yin, Fu Wang, Xujiong Ye, Yanda Meng, Zeyu Fu |
| 2025 | NAACL | Exploring the Cost-Effectiveness of Perspective Taking in Crowdsourcing Subjective Assessment: A Case Study of Toxicity Detection. | Xiaoni Duan, Zhuoyan Li, Chien-Ju Ho, Ming Yin |
| 2025 | PRICAI | Balanced Learning for Incremental Multi-view Clustering. | Lijuan Wang, Feng Chen, Ming Yin, Zhifeng Hao, Ruichu Cai, Wei Chen, Xuan Xiong |
| 2025 | PRICAI | High-Order Information Embedding Transfer for Clustering with Constrained Laplacian Rank. | Lijuan Wang, Wenping Xiong, Guangdong Sun, Ming Yin, Zhifeng Hao, Ruichu Cai, Wei Chen, Minghua Zhao |
| 2024 | AAAI | Decoding AI's Nudge: A Unified Framework to Predict Human Behavior in AI-Assisted Decision Making. | Zhuoyan Li, Zhuoran Lu, Ming Yin |
| 2024 | CHI | The Value, Benefits, and Concerns of Generative AI-Powered Assistance in Writing. | Zhuoyan Li, Chen Liang, Jing Peng, Ming Yin |
| 2024 | CHI | "Are You Really Sure?" Understanding the Effects of Human Self-Confidence Calibration in AI-Assisted Decision Making. | Shuai Ma, Xinru Wang, Ying Lei, Chuhan Shi, Ming Yin, Xiaojuan Ma |
| 2024 | CVPR | MMMU: A Massive Multi-Discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI. | Xiang Yue, Yuansheng Ni, Tianyu Zheng, Kai Zhang, 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 |
| 2024 | EMNLP | How Does the Disclosure of AI Assistance Affect the Perceptions of Writing? | Zhuoyan Li, Chen Liang, Jing Peng, Ming Yin |
| 2024 | ICML | Learning the Target Network in Function Space. | Kavosh Asadi, Yao Liu, Shoham Sabach, Ming Yin, Rasool Fakoor |
| 2024 | ICML | Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games. | Songtao Feng, Ming Yin, Yu-Xiang Wang, Jing Yang, Yingbin Liang |
| 2024 | IJCAI | Designing Behavior-Aware AI to Improve the Human-AI Team Performance in AI-Assisted Decision Making. | Syed Hasan Amin Mahmood, Zhuoran Lu, Ming Yin |
| 2024 | ISIT | Towards General Function Approximation in Nonstationary Reinforcement Learning. | Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang |
| 2024 | IUI | Enhancing AI-Assisted Group Decision Making through LLM-Powered Devil's Advocate. | Chun-Wei Chiang, Zhuoran Lu, Zhuoyan Li, Ming Yin |
| 2024 | IUI | Do Crowdsourced Fairness Preferences Correlate with Risk Perceptions? | Chowdhury Mohammad Rakin Haider, Christopher W. Clifton, Ming Yin |
| 2024 | WWW | Robust Federated Learning Mitigates Client-side Training Data Distribution Inference Attacks. | Yichang Xu, Ming Yin, Minghong Fang, Neil Zhenqiang Gong |
| 2024 | WWW | Poisoning Federated Recommender Systems with Fake Users. | Ming Yin, Yichang Xu, Minghong Fang, Neil Zhenqiang Gong |
| 2024 | SACMAT | ToneCheck: Unveiling the Impact of Dialects in Privacy Policy. | Jay Barot, Ali A. Allami, Ming Yin, Dan Lin |
| 2023 | AAAI | Modeling Human Trust and Reliance in AI-Assisted Decision Making: A Markovian Approach. | Zhuoyan Li, Zhuoran Lu, Ming Yin |
| 2023 | AAAI | On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. | Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora |
| 2023 | ACL | Interactive Concept Learning for Uncovering Latent Themes in Large Text Collections. | Maria Leonor Pacheco, Tunazzina Islam, Lyle H. Ungar, Ming Yin, Dan Goldwasser |
| 2023 | AIES | How does Value Similarity affect Human Reliance in AI-Assisted Ethical Decision Making? | Saumik Narayanan, Guanghui Yu, Chien-Ju Ho, Ming Yin |
| 2023 | CHI | Are Two Heads Better Than One in AI-Assisted Decision Making? Comparing the Behavior and Performance of Groups and Individuals in Human-AI Collaborative Recidivism Risk Assessment. | Chun-Wei Chiang, Zhuoran Lu, Zhuoyan Li, Ming Yin |
| 2023 | CHI | Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness Likelihood to Promote Appropriate Trust in AI-Assisted Decision-Making. | Shuai Ma, Ying Lei, Xinru Wang, Chengbo Zheng, Chuhan Shi, Ming Yin, Xiaojuan Ma |
| 2023 | CHI | Watch Out for Updates: Understanding the Effects of Model Explanation Updates in AI-Assisted Decision Making. | Xinru Wang, Ming Yin |
| 2023 | EMNLP | TheoremQA: A Theorem-driven Question Answering Dataset. | Wenhu Chen, Ming Yin, Max Ku, Pan Lu, Yixin Wan, Xueguang Ma, Jianyu Xu, Xinyi Wang, Tony Xia |
| 2023 | EMNLP | Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations. | Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, Ming Yin |
| 2023 | HCI | Acceptance of Generative AI in the Creative Industry: Examining the Role of AI Anxiety in the UTAUT2 Model. | Ming Yin, Bingxu Han, Sunghan Ryu, Min Hua |
| 2023 | ICLR | Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient. | Ming Yin, Mengdi Wang, Yu-Xiang Wang |
| 2023 | ICML | Non-stationary Reinforcement Learning under General Function Approximation. | Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang |
| 2023 | ICML | Offline Reinforcement Learning with Closed-Form Policy Improvement Operators. | Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai, Yu-Xiang Wang, William Yang Wang |
| 2023 | IJCAI | Strategic Adversarial Attacks in AI-assisted Decision Making to Reduce Human Trust and Reliance. | Zhuoran Lu, Zhuoyan Li, Chun-Wei Chiang, Ming Yin |
| 2023 | IJCAI | 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 |
| 2023 | UAI | No-Regret Linear Bandits beyond Realizability. | Chong Liu, Ming Yin, Yu-Xiang Wang |
| 2022 | AIES | Understanding Decision Subjects' Fairness Perceptions and Retention in Repeated Interactions with AI-Based Decision Systems. | Meric Altug Gemalmaz, Ming Yin |
| 2022 | AIES | Towards Better Detection of Biased Language with Scarce, Noisy, and Biased Annotations. | Zhuoyan Li, Zhuoran Lu, Ming Yin |
| 2022 | AIES | How Does Predictive Information Affect Human Ethical Preferences? | Saumik Narayanan, Guanghui Yu, Wei Tang, Chien-Ju Ho, Ming Yin |
| 2022 | CHI | When Confidence Meets Accuracy: Exploring the Effects of Multiple Performance Indicators on Trust in Machine Learning Models. | Amy Rechkemmer, Ming Yin |
| 2022 | ICLR | Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism. | Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang |
| 2022 | ICML | Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost. | Dan Qiao, Ming Yin, Ming Min, Yu-Xiang Wang |
| 2022 | IUI | Exploring the Effects of Machine Learning Literacy Interventions on Laypeople's Reliance on Machine Learning Models. | Chun-Wei Chiang, Ming Yin |
| 2022 | NAACL | A Holistic Framework for Analyzing the COVID-19 Vaccine Debate. | Maria Leonor Pacheco, Tunazzina Islam, Monal Mahajan, Andrey Shor, Ming Yin, Lyle H. Ungar, Dan Goldwasser |
| 2022 | WWW | The Influences of Task Design on Crowdsourced Judgement: A Case Study of Recidivism Risk Evaluation. | Xiaoni Duan, Chien-Ju Ho, Ming Yin |
| 2022 | WWW | Will You Accept the AI Recommendation? Predicting Human Behavior in AI-Assisted Decision Making. | Xinru Wang, Zhuoran Lu, Ming Yin |
| 2022 | UAI | Offline stochastic shortest path: Learning, evaluation and towards optimality. | Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang |
| 2021 | AISTATS | Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning. | Ming Yin, Yu Bai, Yu-Xiang Wang |
| 2021 | CHI | Human Reliance on Machine Learning Models When Performance Feedback is Limited: Heuristics and Risks. | Zhuoran Lu, Ming Yin |
| 2021 | IJCAI | Accounting for Confirmation Bias in Crowdsourced Label Aggregation. | Meric Altug Gemalmaz, Ming Yin |
| 2021 | IJCAI | Exploring the Effects of Goal Setting When Training for Complex Crowdsourcing Tasks (Extended Abstract). | Amy Rechkemmer, Ming Yin |
| 2021 | IUI | Are Explanations Helpful? A Comparative Study of the Effects of Explanations in AI-Assisted Decision-Making. | Xinru Wang, Ming Yin |
| 2021 | SMC | Video-based AI Decision Support System for Lifting Risk Assessment. | Guoyang Zhou, Vaneet Aggarwal, Ming Yin, Denny Yu |
| 2020 | AAAI | Shared Generative Latent Representation Learning for Multi-View Clustering. | Ming Yin, Weitian Huang, Junbin Gao |
| 2020 | AISTATS | Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning. | Ming Yin, Yu-Xiang Wang |
| 2020 | HCOMP | Does Exposure to Diverse Perspectives Mitigate Biases in Crowdwork? An Explorative Study. | Xiaoni Duan, Chien-Ju Ho, Ming Yin |
| 2020 | HCOMP | Motivating Novice Crowd Workers through Goal Setting: An Investigation into the Effects on Complex Crowdsourcing Task Training. | Amy Rechkemmer, Ming Yin |
| 2020 | WWW | Crowdsourcing Detection of Sampling Biases in Image Datasets. | Xiao Hu, Haobo Wang, Anirudh Vegesana, Somesh Dube, Kaiwen Yu, Gore Kao, Shuo-Han Chen, Yung-Hsiang Lu, George K. Thiruvathukal, Ming Yin |
| 2019 | CHI | Understanding the Effect of Accuracy on Trust in Machine Learning Models. | Ming Yin, Jennifer Wortman Vaughan, Hanna M. Wallach |
| 2019 | ICIG | Deep Stacked Bidirectional LSTM Neural Network for Skeleton-Based Action Recognition. | Kai Zou, Ming Yin, Weitian Huang, Yiqiu Zeng |
| 2019 | WWW | Leveraging Peer Communication to Enhance Crowdsourcing. | Wei Tang, Ming Yin, Chien-Ju Ho |
| 2018 | CHI | Running Out of Time: The Impact and Value of Flexibility in On-Demand Crowdwork. | Ming Yin, Siddharth Suri, Mary L. Gray |
| 2018 | ICONIP | Robust Regression with Nonconvex Schatten p-Norm Minimization. | Deyu Zeng, Ming Yin, Shengli Xie, Zongze Wu |
| 2017 | CHI | Designing for Curiosity: An Interdisciplinary Workshop. | Edith Law, Pierre-Yves Oudeyer, Ming Yin, Mike Schaekermann, Alex C. Williams |
| 2017 | ICIP | Subspace clustering via independent subspace analysis network. | Chunchen Su, Zongze Wu, Ming Yin, Kaixin Li, Weijun Sun |
| 2016 | CHI | Curiosity Killed the Cat, but Makes Crowdwork Better. | Edith Law, Ming Yin, Joslin Goh, Kevin Chen, Michael A. Terry, Krzysztof Z. Gajos |
| 2016 | CVPR | Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds. | Ming Yin, Yi Guo, Junbin Gao, Zhaoshui He, Shengli Xie |
| 2016 | HCOMP | Predicting Crowd Work Quality under Monetary Interventions. | Ming Yin, Yiling Chen |
| 2016 | WWW | The Communication Network Within the Crowd. | Ming Yin, Mary L. Gray, Siddharth Suri, Jennifer Wortman Vaughan |
| 2015 | IJCAI | Bonus or Not? Learn to Reward in Crowdsourcing. | Ming Yin, Yiling Chen |
| 2015 | IJCNN | Low rank sequential subspace clustering. | Yi Guo, Junbin Gao, Feng Li, Stephen Tierney, Ming Yin |
| 2015 | ISNN | Representing Data by Sparse Combination of Contextual Data Points for Classification. | Jingyan Wang, Yihua Zhou, Ming Yin, Shaochang Chen, Benjamin Edwards |
| 2014 | HCOMP | Monetary Interventions in Crowdsourcing Task Switching. | Ming Yin, Yiling Chen, Yuan Sun |
| 2014 | ICASSP | Blocky artifact removal with low-rank matrix recovery. | Ming Yin, Junbin Gao, Yanfeng Sun, Shuting Cai |
| 2014 | IJCNN | Linear Subspace Learning via sparse dimension reduction. | Ming Yin, Yi Guo, Junbin Gao |
| 2013 | AAAI | The Effects of Performance-Contingent Financial Incentives in Online Labor Markets. | Ming Yin, Yiling Chen, Yuan Sun |
| 2013 | HCOMP | Task Sequence Design: Evidence on Price and Difficulty. | Ming Yin, Yiling Chen, Yuan Sun |
| 2013 | ICIP | Restricted Boltzmann machine approach to couple dictionary training for image super-resolution. | Junbin Gao, Yi Guo, Ming Yin |
| 2013 | ICIP | Robust face recognition via double low-rank matrix recovery for feature extraction. | Ming Yin, Shuting Cai, Junbin Gao |
| 2013 | MASS | AWSAN: A Realtime Wireless Sensor Array Platform. | Kai Yu, Ming Yin, Tianxu Du, Liantao Wu, Zhi Wang |
| 2013 | MASS | A Direct Wideband Direction of Arrival Estimation under Compressive Sensing. | Kai Yu, Ming Yin, Ji-an Luo, Ming Bao, Yu Hen Hu, Zhi Wang |
| 2012 | ISCAS | A 100-channel hermetically sealed implantable device for wireless neurosensing applications. | Ming Yin, David A. Borton, Juan Aceros, William R. Patterson, Arto V. Nurmikko |
| 2010 | FAW | Mechanism Design for Multi-slot Ads Auction in Sponsored Search Markets. | Xiaotie Deng, Yang Sun, Ming Yin, Yunhong Zhou |
| 2009 | FAW | A Bit-Parallel Exact String Matching Algorithm for Small Alphabet. | Guomin Zhang, En Zhu, Ling Mao, Ming Yin |
| 2008 | ICNC | A Coevolutionary Model for Stabilizing Collaboration Trust in Supply Chain. | Ming Yin, Songzheng Zhao |
| 2008 | ISCAS | A wideband PWM-FSK receiver for wireless implantable neural recording applications. | Ming Yin, Maysam Ghovanloo |
| 2008 | ISCAS | A clockless ultra low-noise low-power wireless implantable neural recording system. | Ming Yin, Maysam Ghovanloo |
| 2007 | ISCAS | A Low-Noise Preamplifier with Adjustable Gain and Bandwidth for Biopotential Recording Applications. | Ming Yin, Maysam Ghovanloo |
| 2007 | ISCAS | Using Pulse Width Modulation for Wireless Transmission of Neural Signals in a Multichannel Neural Recording System. | Ming Yin, Maysam Ghovanloo |
| 2007 | SNPD | Research on Adaptive Error Concealment for Video Transmission over packet-lossy channel. | Ming Yin, Yun Xie, Fen Guo, Shuting Cai |
| 2007 | SNPD | Improvements on MB-layer Rate Control Scheme for H.264 video Using complexity estimation. | Ming Yin, Yun Xie, Fen Guo, Shuting Cai |
| 2006 | WoWMoM | Middleware Support for Context-Awareness in 4G Environments. | Thomas Springer, Kay Kadner, Frank Steuer, Ming Yin |
| 2005 | ICCSA | On Discovering Concept Entities from Web Sites. | Ming Yin, Dion Hoe-Lian Goh, Ee-Peng Lim |