# Open Meditron: An Auditable Pipeline for Clinical LLMs

> Source: <https://arxiv.org/abs/2605.16215>
> Published: 2026-07-21 10:19:02+00:00

# Computer Science > Artificial Intelligence

[Submitted on 15 May 2026 (

[v1](https://arxiv.org/abs/2605.16215v1)), last revised 29 May 2026 (this version, v2)]# Title:Fully Open Meditron: An Auditable Pipeline for Clinical LLMs

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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.

## Submission history

From: Xavier Theimer-Lienhard [[view email](/show-email/92d2e130/2605.16215)]

**Fri, 15 May 2026 17:29:08 UTC (603 KB)**

[[v1]](/abs/2605.16215v1)**[v2]** Fri, 29 May 2026 15:56:10 UTC (603 KB)

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