Papers by Haochen Zou

1 papers
Iterative Knowledge Graph Refinement and Integration for Medical Question Answering (2026.findings-acl)

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Challenge: Existing graph-based RAG methods heuristically retrieve and refine question-relevant subgraphs, potentially introducing redundant and noisy factual information that is difficult for LLMs to process.
Approach: They propose to integrate knowledge graphs (KGs) through retrieval-augmented generation methods to improve LLM reasoning by incorporating external trustworthy knowledge resources.
Outcome: The proposed framework achieves state-of-the-art against baseline competitors on three medical QA benchmark datasets.

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