MedAction: Towards Active Multi-turn Clinical Diagnostic LLMs

The paper introduces MedAction, a tree‑structured distillation pipeline that generates high‑quality multi‑turn diagnostic trajectories by interacting an LLM with an environment. It identifies three failure modes in current LLMs—ungrounded test ordering, unreliable diagnostic updates, and degraded multi‑turn coherence—and proposes two knowledge‑graph‑grounded metrics, Disease Trajectory Consistency and Reasoning‑Action Consistency, to filter trajectory quality. Using this pipeline, the authors create MedAction‑32K, a dataset of 32,681 trajectories from 2,896 PMC cases, and fine‑tune an 8B model that achieves state‑of‑the‑art performance on MedR‑Bench and the MedAction‑300‑Hard benchmark among open‑source medical LLMs.

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• llms
• fine-tuning
• efficiency
• benchmarks