Article

C-RLM: Schema-Enforced Recursive Synthesis for Auditable, Long-Context Clinical Documentation

2026-01-26

Abstract excerpt

Clinical decision-making for multi-morbid patients requires synthesizing evidence from lengthy, fragmented records—a task that exposes the limitations of standard Retrieval-Augmented Generation (RAG) and long-context Large Language Models (LLMs), which often lose critical information or lack auditability. We introduce the Clinical-Recursive Language Model (C-RLM), a framework that reframes evidence synthesis as a...

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Literature Corpus work: 1e7b8566-e1b7-5d77-86cd-39b08370744d
DOI: 10.64898/2026.01.24.26344761

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