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Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering

arXiv · AI, language, vision and robotics · article · Sep 14, 2026 · UTC

Large language models (LLMs) have been widely adopted for clinical question answering (QA). Current systems can attach citations to their answers, but these often point to broad texts, leaving time-pressed clinicians unable to verify them efficiently. An alternative is to ensure that responses are verifiable by construction: providing fine-grained verbatim quotes from reference material that substantiate claims, so users can verify an answer without opening other documents. In this paper, we evaluate the ability of current models to perform this task end-to-end: from providing citations for ev

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