3 papers
cs.CL2025
RFKG-CoT: Relation-Driven Adaptive Hop-count Selection and Few-Shot Path Guidance for Knowledge-Aware QA
Chao Zhang, Minghan Li, Tianrui Lv +1
Large language models (LLMs) often generate hallucinations in knowledge-intensive QA due to parametric knowledge limitations. While existing methods like KG-CoT improve reliability…
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…
cs.IR2025
Efficient Long-Document Reranking via Block-Level Embeddings and Top-k Interaction Refinement
Minghan Li, Eric Gaussier, Guodong Zhou
Dense encoders and LLM-based rerankers struggle with long documents: single-vector representations dilute fine-grained relevance, while cross-encoders are often too expensive for p…