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Baichuan-M3: Modeling Clinical Inquiry for Reliable Medical Decision-Making

Baichuan-M3 is a medical-enhanced large language model designed for clinical decision support with capabilities in proactive information gathering, long-horizon reasoning, and hallucination suppression.

Year
2026
Venue
arXiv 2026
Authors
18
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arxiv.org/abs/2602.06570ARXIV-DEFAULT
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Abstract

We introduce Baichuan-M3, a medical-enhanced large language model engineered to shift the paradigm from passive question-answering to active, clinical-grade decision support. Addressing the limitations of existing systems in open-ended consultations, Baichuan-M3 utilizes a specialized training pipeline to model the systematic workflow of a physician. Key capabilities include: (i) proactive information acquisition to resolve ambiguity; (ii) long-horizon reasoning that unifies scattered evidence into coherent diagnoses; and (iii) adaptive hallucination suppression to ensure factual reliability. Empirical evaluations demonstrate that Baichuan-M3 achieves state-of-the-art results on HealthBench, the newly introduced HealthBench-Hallu and ScanBench, significantly outperforming GPT-5.2 in clinical inquiry, advisory and safety. The models are publicly available at https://huggingface.co/collections/baichuan-inc/baichuan-m3.

Authors

18