Article

On the robustness of medical term representations in locally deployable language models

2026-02-26

Abstract excerpt

<h4>Structured Abstract</h4> <h4>Background</h4> Hosting large language models (LLMs) on-premises can secure patient data but requires compact architectures to function on standard hardware. The impact of such constraints on the robustness of their representations for medical terminology is important for clinical AI safety but poorly understood. The statistical nature of LLM training inherently limits the repres...

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Literature Corpus work: 454d4cac-4288-585f-94f9-8a345e01d372
DOI: 10.64898/2026.02.24.26346972

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