Article

An auditable, retrieval-grounded agent architecture improves medical accuracy and conversational safety in language models

2026-07-02

Abstract excerpt

<title>Abstract</title> <p>General-purpose language models excel on medical examinations yet remain unreliable in clinical conversation: they guess under uncertainty, lose context, confirm mistaken premises, and resist audit. Asha, a neurosymbolic clinical agent, addresses these through architecture: a general-purpose model wrapped in symbolic stakes-scoring, retrieval grounding, inverse-retrieval falsification,...

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Literature Corpus work: edc645db-4aca-5d50-b0c5-3eb117721510
DOI: 10.21203/rs.3.rs-10206806/v1

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