Papers by Chunli Lv

1 papers
Structure Guided Retrieval-Augmented Generation for Factual Queries (2026.acl-long)

Copied to clipboard

Challenge: Existing methods for RAG produce factually incorrect outputs, resulting in incorrect answers.
Approach: They propose a novel problem that explicitly incorporates structural information into RAG for factual questions to satisfy all query conditions.
Outcome: The proposed method significantly outperforms baselines on ERQA while maintaining reasonable computational overhead.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations