mlsanityData to 14 Oct 2026

ARCagent: An Adaptive Retrieval Calibration Agent for Clinical Question Answering

arXiv 2609.36392 ↗First posted 28 Sep 2026cs.AI cs.IRcited by 0

On the map: Retrieval-augmented generation → Medical and biomedical RAG

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Abstract (arXiv)

In diseases where clinical guidelines are incomplete, contested, or mutually contradictory, knowledge completeness and dynamic conflict-aware synthesis are two safety-critical properties that standard Retrieval-Augmented Generation systems do not provide. Therefore, we present sysname, an adaptive retrieval calibration clinical question-answering agent for ME/CFS, a disease where diagnostic frameworks coexist and major guidelines actively contradict each other on treatment. ARCagent contributes three components. First, a 1,706-chunk, 10-source knowledge base with a structured inter-guideline conflict registry spanning all active ME/CFS diagnostic frameworks. Second, a conflict-aware retrieval calibration pipeline that re-ranks retrieved evidence using query-specific focus and conflict signals. Third, a benchmark scored by LLM-as-Judge, avoiding systematic underestimation averaging 10.1 percentage points caused by keyword matching. ARCagent achieves 95.3%, outperforming all base LLMs. Code is available at https://github.com/Yukyin/ARCagent.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Medical and biomedical RAG, one of 15 directions in Retrieval-augmented generation. Builds on 16 of its 43 references that are in the map. First posted on arXiv 28 Sep 2026.

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16 of 43 references.

References · 16

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  3. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,141
  4. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,839
  5. 2022Large Language Models Encode Clinical Knowledgecited by 1,830
  6. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,375
  7. 2019PubMedQA: A Dataset for Biomedical Research Question Answeringcited by 1,288
  8. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,210
  9. 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 1,011
  10. 2022Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questionscited by 923
  11. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 792
  12. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
4 more
  1. 2020Aligning AI With Shared Human Valuescited by 723
  2. 2023Capabilities of GPT-4 on Medical Challenge Problemscited by 638
  3. 2023HuatuoGPT, towards Taming Language Model to Be a Doctorcited by 214
  4. 2023Do We Still Need Clinical Language Models?cited by 98

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