The Geometry of Queries: Query-Based Innovations in Retrieval-Augmented Generation for Healthcare QA

• URL: http://arxiv.org/abs/2407.18044v2
• Date: Wed, 30 Jul 2025 16:28:54 GMT
• Title: The Geometry of Queries: Query-Based Innovations in Retrieval-Augmented Generation for Healthcare QA
• Authors: Eric Yang, Jonathan Amar, Jong Ha Lee, Bhawesh Kumar, Yugang Jia,
• Abstract summary: QB-RAG is a framework for enhancing Retrieval-Augmented Generation systems in healthcare question-answering.<n>A key component of QB-RAG is an LLM-based filtering mechanism that ensures that only relevant and answerable questions are included in the database.<n>Our empirical evaluation on a healthcare data set demonstrates the superior performance of QB-RAG compared to existing retrieval methods.
• Score: 1.2839205715237014
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Deploying Large Language Models (LLMs) for healthcare question answering requires robust methods to ensure accuracy and reliability. This work introduces Query-Based Retrieval Augmented Generation (QB-RAG), a framework for enhancing Retrieval-Augmented Generation (RAG) systems in healthcare question-answering by pre-aligning user queries with a database of curated, answerable questions derived from healthcare content. A key component of QB-RAG is an LLM-based filtering mechanism that ensures that only relevant and answerable questions are included in the database, enabling reliable reference query generation at scale. We provide theoretical motivation for QB-RAG, conduct a comparative analysis of existing retrieval enhancement techniques, and introduce a generalizable, comprehensive evaluation framework that assesses both the retrieval effectiveness and the quality of the generated response based on faithfulness, relevance, and adherence to the guideline. Our empirical evaluation on a healthcare data set demonstrates the superior performance of QB-RAG compared to existing retrieval methods, highlighting its practical value in building trustworthy digital health applications for health question-answering.

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