I joined the School of Computer Science and Technology at Soochow University in 2024, where I am currently an Associate Professor. My research lies at the intersection of information retrieval, natural language processing, and large language models. I am particularly interested in conversational search and retrieval-augmented generation, memory and reasoning for LLM-based agents, long-document retrieval and reranking, legal AI, and efficient and trustworthy LLM systems.
I received my B.S. degree from Xi’an Jiaotong University, my M.S. degree from Xidian University, and my Ph.D. degree from Université Grenoble Alpes, France, where I was advised by Prof. Eric Gaussier. If you are interested in academic collaboration, student supervision, or research discussions, please feel free to contact me at [email].
🔥 News
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2026.08: 🎉 Our survey paper, A Survey of Long-Document Retrieval in the PLM and LLM Era, has been accepted for publication in ACM Transactions on Information Systems (TOIS).
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2026.08: 🎉 Three papers are accepted by EMNLP 2026: SAGA and Cascade-SC to the Main Conference, and EviRerank to Findings.
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2026.08: 🎉 Retrieval-Feedback Aligned Distillation for Deployable LLM Query Expansion has been accepted as an Oral paper at NLPCC 2026.
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2026.05: 🎉🎉 1 paper is accepted by ACM Transactions on Information Systems (TOIS):
Query Expansion in the Age of Pre-trained and Large Language Models: A Comprehensive Survey,
authors: Minghan Li, Xinxuan Lv, Junjie Zou, Tongna Chen, Chao Zhang, Suchao An, Ercong Nie, Guodong Zhou.
📝 Selected Publications
* Corresponding author; † Co-first author.
Minghan Li*, Ercong Nie, Huiping Huang, Xinxuan Lv, Guodong Zhou
Information Fusion, 2026 (JCR Q1, CAAI-A journal, IF 17.4)
- Robust query expansion and rank fusion via dual-layer prompt ensembles.
GLIER: Generative Legal Inference and Evidence Ranking for Legal Case Retrieval
Minghan Li*†, Tianrui Lv†, Chao Zhang, Guodong Zhou
ACL 2026 Main Conference
- Generative legal inference and evidence ranking for legal case retrieval.
S2G-RAG: Structured Sufficiency and Gap Judging for Iterative Retrieval-Augmented QA
Minghan Li*†, Junjie Zou†, Xinxuan Lv, Chao Zhang, Guodong Zhou
ACL 2026 Main Conference
- Iterative RAG with structured sufficiency judgment and gap-guided retrieval.
The Power of Selecting Key Blocks with Local Pre-ranking for Long Document Information Retrieval
Minghan Li, Diana Nicoleta Popa, Johan Chagnon, Yagmur Gizem Cinar, Eric Gaussier
ACM Transactions on Information Systems, 2023 (JCR Q1, CCF-A journal, IF 11.2)
- Key-block selection with local pre-ranking for long-document retrieval.
📚 Conference and Journal Papers
* Corresponding author; † Co-first author.
- TOIS 2026 A Survey of Long-Document Retrieval in the PLM and LLM Era
- TOIS 2026 Query Expansion in the Age of Pre-trained and Large Language Models: A Comprehensive Survey
- Information Fusion 2026 Dual-Layer Prompt Ensembles: Leveraging System-and User-Level Instructions for Robust LLM-Based Query Expansion and Rank Fusion
- ACL 2026 Main Conference GLIER: Generative Legal Inference and Evidence Ranking for Legal Case Retrieval
- ACL 2026 Main Conference S2G-RAG: Structured Sufficiency and Gap Judging for Iterative Retrieval-Augmented QA
- EMNLP 2026 Main Conference SAGA: Structured Applicability-Guided Alignment for Conversational Legal Retrieval
- EMNLP 2026 Main Conference Cascade-SC: A Pareto-Efficient Cross-Model Cascade for Test-Time Reasoning
- EMNLP 2026 Findings EviRerank: Adaptive Evidence Construction for Long-Document LLM Reranking
- NLPCC 2026 Conference Oral Retrieval-Feedback Aligned Distillation for Deployable LLM Query Expansion
- AAAI 2026 RFKG-CoT: Relation-Driven Adaptive Hop-count Selection and Few-Shot Path Guidance for Knowledge-Aware QA
- COLING 2024 Domain Adaptation for Dense Retrieval and Conversational Dense Retrieval through Self-Supervision by Meticulous Pseudo-Relevance Labeling
- TOIS 2023 The Power of Selecting Key Blocks with Local Pre-ranking for Long Document Information Retrieval
- SIGIR 2022 BERT-based Dense Intra-ranking and Contextualized Late Interaction via Multi-task Learning for Long Document Retrieval
- AAAI 2022 Listwise Learning to Rank Based on Approximate Rank Indicators
- SIGIR 2021 KeyBLD: Selecting Key Blocks with Local Pre-ranking for Long Document Information Retrieval
- ICPR 2020 Learning to Rank for Active Learning: A Listwise Approach
🗂 Preprints and Surveys
arXiv 2026Automatic In-Domain Exemplar Construction and LLM-Based Refinement of Multi-LLM Expansions for Query Expansion, Minghan Li, Ercong Nie, Siqi Zhao, Tongna Chen, Huiping Huang, Guodong ZhouarXiv 2026GenState-AI: State-Aware Dataset for Text-to-Video Retrieval on AI-Generated Videos, Minghan Li, Tongna Chen, Tianrui Lv, Yishuai Zhang, Suchao An, Guodong ZhouarXiv 2026Retrieval-Feedback-Driven Distillation and Preference Alignment for Efficient LLM-based Query Expansion, Minghan Li, Guodong ZhouarXiv 2025Enhanced Retrieval of Long Documents: Leveraging Fine-Grained Block Representations with Large Language Models, Minghan Li, Eric Gaussier, Guodong Zhou
💰 Research Grants
- National Natural Science Foundation of China (NSFC) grant: Research on Causality-Enhanced Memory Mechanisms for Long-Term Conversational Agents, Principal Investigator.
- Soochow University Academic Start-up Fund, Principal Investigator.
- 2023 — Domain Transfer for Conversational Search, IDEX Université Grenoble Alpes, for a research visit to the National University of Singapore (NUS), Principal Investigator.
📖 Educations
- 2020.10 - 2023.12, Ph.D. in Computer Science,
Université Grenoble Alpes, France. - M.S. in Computer Technology,
Xidian University, China. - B.S. in Information Engineering,
Xi’an Jiaotong University, China.