3 papers
cs.IR2026
Query Expansion in the Age of Pre-trained and Large Language Models: A Comprehensive Survey
Minghan Li, Xinxuan Lv, Junjie Zou +5
Modern information retrieval must reconcile short, ambiguous queries with increasingly diverse and dynamic corpora. Query expansion (QE) remains a core technique for mitigating voc…
cs.IR2026
Automatic In-Domain Exemplar Construction and LLM-Based Refinement of Multi-LLM Expansions for Query Expansion
Minghan Li, Ercong Nie, Siqi Zhao +3
Query expansion with large language models is promising but often relies on hand-crafted prompts, manually chosen exemplars, or a single LLM, making it non-scalable and sensitive t…
cs.IR2025
A Survey of Long-Document Retrieval in the PLM and LLM Era
Minghan Li, Miyang Luo, Tianrui Lv +4
The proliferation of long-form documents presents a fundamental challenge to information retrieval (IR), as their length, dispersed evidence, and complex structures demand speciali…