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Technical University of Munich and TUM University Hospital
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LLM agents can leap from 40% to 88% accuracy in complex clinical tasks simply by validating new skills against a regression budget, proving that *how* you learn matters more than *what* you learn.
A retrieval-augmented generation system that grounds LLM responses in authoritative guideline content that significantly outperformed the standalone LLM in all metrics and suggest that grounded RAG systems have significant potential to enhance clinical guideline accessibility but require further validation before clinical deployment.
