Biometrics improve personalized memory for shared AI assistants
Personalizing LLM Agent Memory Using Biometrics
Artificial Intelligence
Summary
Personalized memory helps AI assistants remember users better, but when multiple people share the same assistant, it can get confused about who said what. The researchers created Bio-Memory, a system that uses biometric data like face or palm prints to match memories specifically to the right user. This makes the AI better at recalling information tied to each person, even when many people use it. Tests showed that combining biometric matching with memory search significantly improves accuracy in identifying the correct user’s data.
Large language modelsPersonalized memoryBiometricsSemantic similarityFace recognitionPalmprint recognitionMemory retrievalShared AI agentsF1 scoreBLEU score
Authors
Yanhong Qian, Qingguo Meng, Shihao Ding, Xingbo Dong, Zhe Jin, Hanrui Wang, Isao Echizen
Abstract
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 retrieval candidate pool before semantic ranking. We evaluate Bio-Memory on LoCoMo in a 10-user shared-agent setting over 7 face benchmarks and 10 palmprint protocols. Across datasets, Bio-Memory consistently separates owner and non-owner queries. Under face-based personalization, the largest average gap reaches 27.29% / 21.15% in F1 / BLEU-1 on CALFW; under palmprint-based personalization, the corresponding gap is 25.75% / 19.22% on MS_Blue. These results support biometrics as a practical control signal for personalized memory retrieval in shared environments.