Hang Li

Hang Li

Ph.D. Candidate, Michigan State University
LLMs · Multi-Agent Systems · AI for Education

Curriculum Vitae

Download the PDF version

Research Interests

Education

Research Experience

Honors & Awards

Grant Writing

Presentations

Invited Talks

Conference Oral Presentations

Tutorials

Teaching

Mentoring

Professional Service

Organizer

Program Committee Member & Conference Reviewer

Journal Reviewer

External Reviewer

Media Coverage

Publications

* denotes equal contribution. See the publications page for links.

Preprints and Submissions

  1. Hang Li, Kaiqi Yang, Yucheng Chu, Yue Xing, Hui Liu. Rubric Optimization for LLM-Based Automated Grading with Data Synthesis. Under review, 2026.
  2. Yingqian Cui, Wei Deng, Lantao Mei, Hang Li, Charu C. Aggarwal, Hui Liu, Yue Xing. Planner-Guided Recursive Exploration for Diffusion Language Model Decoding. Under review, 2026.
  3. Hongji Pu, Hang Li, Yucheng Chu, Jiliang Tang. RubricWorld: World Model-Guided Rubric Optimization for LLM Graders. Under review, 2026.
  4. Kaiqi Yang, Hang Li, Xianxuan Long, Fedor Filippov, Yucheng Chu, Yasemin Copur-Gencturk, Peng He, Cory Susanne Miller, Namsoo Shin, Joseph Krajcik, Hui Liu. How Uncertain Is the Grade? A Benchmark of Uncertainty Metrics for LLM-Based Automatic Assessment. Under review, 2026.
  5. Yucheng Chu, Haoyu Han, Shen Dong, Hang Li, Kaiqi Yang, Yasemin Copur-Gencturk, Joseph Krajcik, Namsoo Shin, Hui Liu. From Flat to Structural: Enhancing Automated Short Answer Grading with GraphRAG. arXiv preprint, 2026.
  6. Yi-Fan Zhang, Hang Li, Dingjie Song, Lichao Sun, Tianlong Xu, Qingsong Wen. From Correctness to Comprehension: AI Agents for Personalized Error Diagnosis in Education. arXiv preprint, 2025.
  7. Hang Li, Tianlong Xu, Jiliang Tang, Qingsong Wen. Knowledge Tagging System on Math Questions via LLMs with Flexible Demonstration Retriever. arXiv preprint, 2024.
  8. Hang Li, Tianlong Xu, Jiliang Tang, Qingsong Wen. Automate Knowledge Concept Tagging on Math Questions with LLMs. arXiv preprint, 2024.
  9. Hang Li, Tianlong Xu, Chaoli Zhang, Eason Chen, Jing Liang, Xing Fan, Haoyang Li, Jiliang Tang, Qingsong Wen. Bringing Generative AI to Adaptive Learning in Education. arXiv preprint, 2024.
  10. Wenzhuo Tang, Renming Liu, Hongzhi Wen, Xinnan Dai, Jiayuan Ding, Hang Li, Wenqi Fan, Yuying Xie, Jiliang Tang. A General Single-Cell Analysis Framework via Conditional Diffusion Generative Models. bioRxiv preprint, 2023.

Conference Papers

  1. Hang Li, Kaiqi Yang, Yucheng Chu, Hui Liu, Jiliang Tang. Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving. Findings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2026.
  2. Hang Li, Fedor Filippov, Yuling Lin, Pengfei He, Kaiqi Yang, Yucheng Chu, Yingqian Cui, Hui Liu, Jiliang Tang. “**Important** You Should Give Me Full Credits!”: Exploring Prompt Injection Attacks on LLM-Based Automatic Grading Systems. Findings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2026.
  3. Hang Li, Kaiqi Yang, Yucheng Chu, Ahreum Han, Rui Meng, Yasemin Copur-Gencturk, Hui Liu. i-VIP: A LLM-Driven Multi-Agent System for Professional Development of Mathematics Teachers. International Conference on Artificial Intelligence in Education (AIED), 2026. Oral
  4. Yucheng Chu, Hang Li, Kaiqi Yang, Yasemin Copur-Gencturk, Kevin Haudek, Joseph Krajcik, Namsoo Shin, Jiliang Tang. Optimizing In-Context Demonstrations for LLM-Based Automated Grading. International Conference on Artificial Intelligence in Education (AIED), 2026. Oral
  5. Yucheng Chu, Hang Li, Kaiqi Yang, Yasemin Copur-Gencturk, Joseph Krajcik, Namsoo Shin, Jiliang Tang. Confusion-Aware Rubric Optimization for LLM-Based Automated Grading. International Conference on Educational Data Mining (EDM), 2026.
  6. Yibo Yan, Shen Wang, Jiahao Huo, Hang Li, Boyan Li, Jiamin Su, Xiong Gao, Yifan Zhang, Tianlong Xu, Zhendong Chu, et al.. ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models via Error Detection. Findings of the Association for Computational Linguistics (ACL), 2026.
  7. Haoyu Han, Kai Guo, Harry Shomer, Yu Wang, Yucheng Chu, Hang Li, Li Ma, Jiliang Tang. Reasoning by Exploration: A Unified Approach to Retrieval and Generation over Graphs. Proceedings of the ACM Web Conference (WWW), 2026.
  8. Hang Li, Yucheng Chu, Kaiqi Yang, Yasemin Copur-Gencturk, Jiliang Tang. LLM-Based Automated Grading with Human-in-the-Loop. IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 2025.
  9. Kaiqi Yang, Hang Li, Yucheng Chu, Zitao Liu, Mi Tian, Hui Liu. Iterative LLM-Based Generation and Refinement of Distracting Conditions in Math Word Problems. IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 2025.
  10. Juanhui Li, Tingting Li, Hang Li, Haoyu Han, Pengfei He, Peng He, Hui Liu. Human-AI Collaboration for Knowledge-in-Use Assessment Design: Leveraging LLMs with RAG. IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 2025.
  11. Hang Li, Tianlong Xu, Kaiqi Yang, Yucheng Chu, Yanling Chen, Yichi Song, Qingsong Wen, Hui Liu. Ask-Before-Detection: Identifying and Mitigating Conformity Bias in LLM-Powered Error Detector for Math Word Problem Solutions. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025.
  12. Hang Li, Tianlong Xu, Ethan Chang, Qingsong Wen. Knowledge Tagging with Large Language Model Based Multi-Agent System. Proceedings of the 37th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2025. Innovative Application Award
  13. Yucheng Chu*, Hang Li*, Kaiqi Yang, Harry Shomer, Hui Liu, Yasemin Copur-Gencturk, Jiliang Tang. A LLM-Powered Automatic Grading Framework with Human-Level Guidelines Optimization. International Conference on Educational Data Mining (EDM), 2025.
  14. Yucheng Chu, Peng He, Hang Li, Haoyu Han, Kaiqi Yang, Yu Xue, Tingting Li, Joseph Krajcik, Jiliang Tang. Enhancing LLM-Based Short Answer Grading with Retrieval-Augmented Generation. International Conference on Educational Data Mining (EDM), 2025.
  15. Hang Li, Wei Jin, Geri Skenderi, Harry Shomer, Wenzhuo Tang, Wenqi Fan, Jiliang Tang. Sub-graph Based Diffusion Model for Link Prediction. Learning on Graphs Conference (LoG), 2024.
  16. Kaiqi Yang, Yucheng Chu, Taylor Darwin, Ahreum Han, Hang Li, Hongzhi Wen, Yasemin Copur-Gencturk, Jiliang Tang, Hui Liu. Content Knowledge Identification with Multi-Agent Large Language Models (LLMs). International Conference on Artificial Intelligence in Education (AIED), 2024.
  17. Kaiqi Yang, Hang Li, Hongzhi Wen, Tai-Quan Peng, Jiliang Tang, Hui Liu. Are Large Language Models (LLMs) Good Social Predictors?. Findings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
  18. Wenqi Fan, Chengyi Liu, Yunqing Liu, Jiatong Li, Hang Li, Hui Liu, Jiliang Tang, Qing Li. Generative Diffusion Models on Graphs: Methods and Applications. Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023.
  19. Yu Kang, Tianqiao Liu, Hang Li, Yang Hao, Wenbiao Ding, Zitao Liu. Self-Supervised Audio-and-Language Pre-training with Extremely Low-Resource Parallel Data. Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI), 2022.
  20. Hang Li, Yu Kang, Tianqiao Liu, Wenbiao Ding, Zitao Liu. CTAL: Pre-training Cross-modal Transformer for Audio-and-Language Representations. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021.
  21. Tianqiao Liu, Qiang Fang, Wenbiao Ding, Hang Li, Zhongqin Wu, Zitao Liu. Mathematical Word Problem Generation from Commonsense Knowledge Graph and Equations. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021.
  22. Hang Li, Wenbiao Ding, Zhongqin Wu, Zitao Liu. Learning Fine-Grained Multimodal Alignment for Speech Emotion Recognition. Annual Conference of the International Speech Communication Association (INTERSPEECH), 2021.
  23. Hang Li, Yu Kang, Yang Hao, Wenbiao Ding, Zhongqin Wu, Zitao Liu. A Multimodal Machine Learning Framework for Teacher Vocal Delivery Evaluation. International Conference on Artificial Intelligence in Education (AIED), 2021.
  24. Yang Hao, Hang Li, Wenbiao Ding, Zhongqin Wu, Zitao Liu. Multi-Task Learning Based Online Dialogic Instruction Detection with Pre-trained Language Models. International Conference on Artificial Intelligence in Education (AIED), 2021.
  25. Jiahao Chen, Hang Li, Wenbiao Ding, Zhongqin Wu, Zitao Liu. An Educational System for Personalized Teacher Recommendation in K-12 Online Classrooms. International Conference on Artificial Intelligence in Education (AIED), 2021.
  26. Hang Li, Wenbiao Ding, Songfan Yang, Zitao Liu. Identifying At-Risk K-12 Students in Multimodal Online Environments: A Machine Learning Approach. International Conference on Educational Data Mining (EDM), 2020.
  27. Hang Li, Zhiwei Wang, Jiliang Tang, Wenbiao Ding, Zitao Liu. Siamese Neural Networks for Class Activity Detection. International Conference on Artificial Intelligence in Education (AIED), 2020.
  28. Hang Li, Yu Kang, Wenbiao Ding, Song Yang, Songfan Yang, Gale Yan Huang, Zitao Liu. Multimodal Learning for Classroom Activity Detection. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020.
  29. Jiahao Chen, Hang Li, Wenxin Wang, Wenbiao Ding, Gale Yan Huang, Zitao Liu. A Multimodal Alerting System for Online Class Quality Assurance. International Conference on Artificial Intelligence in Education (AIED), 2019.

Journal Articles

  1. Nickolina Yankova, Jinhyo Cho, Hang Li, Kaiqi Yang, Yasemin Copur-Gencturk, Jiliang Tang. Designing Professional Development in Mathematics Teacher Education with AI as a Facilitator: A Roadmap Grounded in High-Quality Professional Development Features. Journal of Mathematics Teacher Education (JMTE), 2026.
  2. Yasemin Copur-Gencturk, Kyle Moreno, Yucheng Chu, Hang Li, Jiliang Tang. Automated Coding of Content and Pedagogical Content Knowledge of Mathematics Using a Multi-Agent Large Language Model. ZDM – Mathematics Education, 2026.
  3. Tai-Quan Peng, Kaiqi Yang, Sanguk Lee, Hang Li, Yucheng Chu, Yuping Lin, Hui Liu. Beyond Partisan Leaning: A Comparative Analysis of Political Bias in Large Language Models. Journal of Information Technology & Politics, 2026.
  4. Shen Wang*, Tianlong Xu*, Hang Li*, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, Qingsong Wen. Large Language Models for Education: A Survey and Outlook. IEEE Signal Processing Magazine (SPM), 2025. 500+ citations
  5. Geri Skenderi, Hang Li, Jiliang Tang, Marco Cristani. Graph-Level Representation Learning with Joint-Embedding Predictive Architectures. Transactions on Machine Learning Research (TMLR), 2024.
  6. Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang. Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs. ACM SIGKDD Explorations Newsletter, 2024. 450+ citations

Workshop Papers

  1. Hang Li, Yichi Zhang, Chenyang Zhu, Anoop Kumar, Daben Liu. MEMO: Memory-Guided Error Momentum for Prompt Optimization in Long-Context Reasoning. NeurIPS Workshop on Test-time Continual Learning Agents, 2026.

Book Chapters

  1. Hang Li, Tianlong Xu, Qingsong Wen. Leverage LLMs on Knowledge Tagging for Math Questions in Education. Future of Learning with Large Language Models, CRC Press, 2025.

Tutorials

  1. Hang Li, Kaiqi Yang, Yucheng Chu, Jiliang Tang. Bringing Generative Artificial Intelligence (GenAI) to Education. International Conference on Educational Data Mining (EDM), 2025.

Patents

  1. Hang Li, Wenbiao Ding, Zitao Liu. Speaker recognition method, electronic device, and storage medium. US Patent US11676609B2, granted 12/2022.