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MedARC Agentic Medical Fact Verifier

An open-source reproduction of Baichuan-M3's medical fact verification system, built by MedARC.

Under active development.

System Sketch

Following Baichuan-M3, the task is split into three models across four steps:

  1. Claim Decomposer breaks input text (answers, documents, reasoning traces, model outputs) into individual medical claims.
  2. Fact Verifier compares each claim against a database of previously fact-checked claims ("Claim X is supported by evidence set Y [under scope Z] as of date T").
  3. For a new claim, a Search Agent is dispatched to find supporting or contradictory evidence from a curated medical corpus.
  4. Results return to the Fact Verifier, which scores the claim on a five-level scale (strongly supported, weakly supported, unclear, weakly unsubstantiated, strongly unsubstantiated) and writes a new entry to the fact database.

Components

Component Role Workspace
baseline End-to-end pipeline on off-the-shelf LLMs (no training) Independent
decomposer Long-form text → atomic medical claims Yes
verifier Claim + evidence → five-level supported↔unsubstantiated score Yes
search Claim → supporting / contradictory sources Yes
datasets Dataset ingestion, construction, and synthetic data Yes
utils Shared helpers used across AMFV packages Yes
training Training experiments and recipes for the above Independent

The Workspace column marks membership in the root uv workspace. Independent packages (baseline, training) are excluded so they can evolve on their own.

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Agentic Medical Fact Verifier

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