Papers by Gongbo Zhang

2 papers
Improving Retrieval-Augmented Generation without Taxonomy-based Error Categorization (2026.acl-short)

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Challenge: Recent work implicitly assumes reliable critic feedback and focuses on planning strategies, while paying limited attention to the robustness of the error correction process itself.
Approach: They propose a response-action learning paradigm that maps flawed RAG outputs to error-mitigating action plans without explicit criticism.
Outcome: The proposed model improves the factual accuracy of large language model outputs without explicit error categorization.
Natural Language Processing in Support of Evidence-based Medicine: A Scoping Review (2025.findings-acl)

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Challenge: Evidence-based medicine (EBM) is at the forefront of modern healthcare, emphasizing the use of the best available scientific evidence to guide clinical decisions.
Approach: They propose to investigate the use of Natural Language Processing (NLP) techniques to identify, appraise, synthesize, apply, and disseminate evidence in EBM.
Outcome: The proposed methods support the five fundamental steps of EBM—Ask, Acquire, Appraise, Apply, and Assess.

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