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

  • 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).

  • 2026.08:  🎉 Three papers are accepted by EMNLP 2026: SAGA and Cascade-SC to the Main Conference, and EviRerank to Findings.

  • 2026.08:  🎉 Retrieval-Feedback Aligned Distillation for Deployable LLM Query Expansion has been accepted as an Oral paper at NLPCC 2026.

  • 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.

Information Fusion 2026
Dual-Layer Prompt Ensembles

Dual-Layer Prompt Ensembles: Leveraging System-and User-Level Instructions for Robust LLM-Based Query Expansion and Rank Fusion

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.
ACL 2026
GLIER

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.
ACL 2026
S2G-RAG

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.
TOIS 2023
TOIS 2023

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
    Minghan Li*, Yishuai Zhang, Tianrui Lv, Siqi Zhao, Miyang Luo, Ercong Nie, Guodong Zhou (JCR Q1, CCF-A journal, IF 11.2)
  • TOIS 2026 Query Expansion in the Age of Pre-trained and Large Language Models: A Comprehensive Survey
    Minghan Li*, Xinxuan Lv, Junjie Zou, Tongna Chen, Chao Zhang, Suchao An, Ercong Nie, Guodong Zhou (JCR Q1, CCF-A journal, IF 11.2)
  • Information Fusion 2026 Dual-Layer Prompt Ensembles: Leveraging System-and User-Level Instructions for Robust LLM-Based Query Expansion and Rank Fusion
    Minghan Li*, Ercong Nie, Huiping Huang, Xinxuan Lv, Guodong Zhou (JCR Q1, CAAI-A journal, IF 17.4)
  • ACL 2026 Main Conference GLIER: Generative Legal Inference and Evidence Ranking for Legal Case Retrieval
    Minghan Li*†, Tianrui Lv, Chao Zhang, Guodong Zhou
  • ACL 2026 Main Conference S2G-RAG: Structured Sufficiency and Gap Judging for Iterative Retrieval-Augmented QA
    Minghan Li*†, Junjie Zou, Xinxuan Lv, Chao Zhang, Guodong Zhou
  • EMNLP 2026 Main Conference SAGA: Structured Applicability-Guided Alignment for Conversational Legal Retrieval
    Xinxuan Lv, Minghan Li*†, Guodong Zhou
  • EMNLP 2026 Main Conference Cascade-SC: A Pareto-Efficient Cross-Model Cascade for Test-Time Reasoning
    Minghan Li*†, Siqi Zhao, Luoliang Hua, Guodong Zhou
  • EMNLP 2026 Findings EviRerank: Adaptive Evidence Construction for Long-Document LLM Reranking
    Minghan Li*, Eric Gaussier, Juntao Li, Guodong Zhou
  • NLPCC 2026 Conference Oral Retrieval-Feedback Aligned Distillation for Deployable LLM Query Expansion
    Minghan Li, Guodong Zhou
  • AAAI 2026 RFKG-CoT: Relation-Driven Adaptive Hop-count Selection and Few-Shot Path Guidance for Knowledge-Aware QA
    Chao Zhang, Minghan Li*, Tianrui Lv, Guodong Zhou
  • COLING 2024 Domain Adaptation for Dense Retrieval and Conversational Dense Retrieval through Self-Supervision by Meticulous Pseudo-Relevance Labeling
    Minghan Li, Eric Gaussier
  • TOIS 2023 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 (JCR Q1, CCF-A journal, IF 11.2)
  • SIGIR 2022 BERT-based Dense Intra-ranking and Contextualized Late Interaction via Multi-task Learning for Long Document Retrieval
    Minghan Li, Eric Gaussier
  • AAAI 2022 Listwise Learning to Rank Based on Approximate Rank Indicators
    Thibaut Thonet, Yagmur Gizem Cinar, Éric Gaussier, Minghan Li, Jean-Michel Renders
  • SIGIR 2021 KeyBLD: Selecting Key Blocks with Local Pre-ranking for Long Document Information Retrieval
    Minghan Li, Eric Gaussier
  • ICPR 2020 Learning to Rank for Active Learning: A Listwise Approach
    Minghan Li, Xialei Liu, Joost van de Weijer, Bogdan Raducanu

🗂 Preprints and Surveys

  • arXiv 2026 Automatic 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 Zhou
  • arXiv 2026 GenState-AI: State-Aware Dataset for Text-to-Video Retrieval on AI-Generated Videos, Minghan Li, Tongna Chen, Tianrui Lv, Yishuai Zhang, Suchao An, Guodong Zhou
  • arXiv 2026 Retrieval-Feedback-Driven Distillation and Preference Alignment for Efficient LLM-based Query Expansion, Minghan Li, Guodong Zhou
  • arXiv 2025 Enhanced 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.
  • 2023Domain 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.