@inproceedings{zhang-etal-2026-pubmed,
    title = "{P}ub{M}ed Reasoner: Dynamic Reasoning-based Retrieval for Evidence-Grounded Biomedical Question Answering",
    author = "Zhang, Yiqing  and
      Liu, Xiaozhong  and
      Murai, Fabricio",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.acl-long.763/",
    pages = "16753--16763",
    ISBN = "979-8-89176-390-6",
    abstract = "Trustworthy biomedical question answering (QA) systems must not only provide accurate answers but also justify them with current, verifiable evidence. Retrieval-augmented approaches partially address this gap but lack mechanisms to iteratively refine poor queries, whereas self-reflection methods kick in only after full retrieval is completed. In this context, we introduce PubMed Reasoner, a biomedical QA agent composed of three stages: **self-critic query refinement** evaluates MeSH terms for coverage, alignment, and redundancy to enhance PubMed queries based on partial (metadata) retrieval; **reflective retrieval** processes articles in batches until sufficient evidence is gathered; and **evidence-grounded response generation** produces answers with explicit citations. PubMed Reasoner with a GPT-4o backbone achieves **78.32{\%}** accuracy on PubMedQA, slightly surpassing human experts, and showing consistent gains on MMLU Clinical Knowledge. Moreover, LLM-as-judge evaluations prefer our responses across: reasoning soundness, evidence grounding, clinical relevance, and trustworthiness. By orchestrating retrieval-first reasoning over authoritative sources, our approach provides practical assistance to clinicians and biomedical researchers while controlling compute and token costs."
}