[2605.16215] Fully Open Meditron: An Auditable Pipeline for Clinical LLMs

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arXiv:2605.16215 (cs)

[Submitted on 15 May 2026 (v1), last revised 29 May 2026 (this version, v2)]

Title:Fully Open Meditron: An Auditable Pipeline for Clinical LLMs

Authors:Xavier Theimer-Lienhard, Mushtaha El-Amin, Fay Elhassan, Sahaj Vaidya, Victor Cartier-Negadi, David Sasu, Lars Klein, Mary-Anne Hartley<br>View a PDF of the paper titled Fully Open Meditron: An Auditable Pipeline for Clinical LLMs, by Xavier Theimer-Lienhard and 7 other authors

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Abstract:Clinical decision support systems (CDSS) require scrutable, auditable pipelines that enable rigorous, reproducible validation. Yet current LLM-based CDSS remain largely opaque. Most "open" models are open-weight only, releasing parameters while withholding the data provenance, curation procedures, and generation pipelines that determine model behavior. Fully Open (FO) models, which expose the complete training stack end-to-end, do not currently exist in medicine. We introduce Fully Open Meditron, the first fully open pipeline for building LLM-CDSS, comprising a clinician-audited training corpus, a reproducible data construction and training framework, and a use-aligned evaluation protocol. The corpus unifies eight public medical QA datasets into a normalized conversational format and expands coverage with three clinician-vetted synthetic extensions: exam-style QA, guideline-grounded QA derived from 46,469 clinical practice guidelines, and clinical vignettes. The pipeline enforces system-wide decontamination, gold-label resampling of teacher generations, and end-to-end validation by a four-physician panel. We evaluate using an LLM-as-a-judge protocol over expert-written clinical vignettes, calibrated against 204 human raters. We apply the recipe to five FO base models (Apertus-70B/8B-Instruct, OLMo-2-32B-SFT, EuroLLM-22B/9B-Instruct). All MeditronFO variants are preferred over their bases. Apertus-70B-MeditronFO improves +6.6 points over its base (47.2% to 53.8%) on aggregate medical benchmarks, establishing a new FO SoTA. Gemma-3-27B-MeditronFO is preferred over MedGemma in 58.6% of LLM-as-a-judge comparisons and outperforms it on HealthBench (58% vs 55.9%). These results show that fully open pipelines can achieve state-of-the-art domain-specific performance without sacrificing auditability or reproducibility.

Comments:<br>Preprint. 31 pages, 10 figures. Code, models, and data: this https URL

Subjects:

Artificial Intelligence (cs.AI); Computation and Language (cs.CL)

Cite as:<br>arXiv:2605.16215 [cs.AI]

(or<br>arXiv:2605.16215v2 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2605.16215

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arXiv-issued DOI via DataCite

Submission history<br>From: Xavier Theimer-Lienhard [view email]<br>[v1]<br>Fri, 15 May 2026 17:29:08 UTC (603 KB)

[v2]<br>Fri, 29 May 2026 15:56:10 UTC (603 KB)

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