SOURCE-LINKED INTELLIGENCE
Personalizing LLM Agent Memory Using Biometrics
Personalized memory helps LLM agents deliver stable, tailored assistance by storing and reusing user-specific data across interactions. In multi-user scenarios, however, retrieval must consider not only semantic similarity but also whether the current requester matches the identity associated with the stored memory. We propose Bio-Memory, a biometric-aware memory architecture that conditions memory retrieval on both semantic similarity and biometric matching. Built on top of A-Mem, Bio-Memory augments each atomic memory note with a biometric embedding and uses biometric matching to form the re
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-08T10:46:12.000Z
First collected: 2026-09-20T20:02:11.508Z. This is not the publication date.