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Toward Workflow-Aware Benchmarking for Healthcare NLP Agents

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

Large language model (LLM) agents are increasingly proposed for healthcare tasks such as clinical documentation, evidence retrieval, patient messaging, and care coordination. Yet many evaluations remain limited to static medical question answering or one-shot generation, under-representing longitudinal state, interruptions, and human handoffs. We introduce an episode-level evaluation protocol for healthcare NLP agents. The protocol separates evidence across model, agent, and simulated-workflow behavior; specifies a five-field episode schema; and defines annotation and scoring for state continu

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First collected: 2026-09-21T06:21:59.299Z. This is not the publication date.