SOURCE-LINKED INTELLIGENCE
Not the Same Protector: Deployment-Dependent Protective Intervention in LLMs
We ask whether a model protects a user in the same way when that user speaks rather than types. Using a single distress vignette---a physical injury of unstated severity following an interpersonal conflict---we present four frontier models with matched inputs across voice, text, and raw API deployment conditions (n=30 per cell) and code each response along five binary protective indicators, including whether the model issues an explicit medical-care directive. Voice-interface responses are markedly shorter than text-interface responses for three of the four models, and protective behavior cont
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-29T08:25:30.000Z
First collected: 2026-09-21T07:51:58.603Z. This is not the publication date.