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LightMem-Ego: Your AI Memory for Everyday Life

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Papers
arxiv:2607.11487

LightMem-Ego: Your AI Memory for Everyday Life

Published on Jul 13
· Submitted by
Ningyu Zhang
on Jul 14
Authors:
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Abstract

Personal AI assistants on mobile and wearable devices continuously perceive users' daily lives through visual and audio streams. However, answering queries about past experiences requires lightweight multimodal memory that can continuously accumulate, organize, and retrieve long-term experiences, which remains challenging. To address this challenge, we present LightMem-Ego, a lightweight streaming multimodal memory system for everyday-life assistance. The system continuously captures egocentric visual and audio streams, aligns them on a shared timeline, and organizes them into a hierarchical memory consisting of current, short-term, and long-term memory. Given a user query, LightMem-Ego dynamically routes retrieval to the appropriate memory level and generates answers grounded in multimodal evidence. The demonstration can be deployed on smartphones and AI glasses, supporting object finding, conversation recall, life summarization, routine discovery, and personalized assistance. Code is available at https://github.com/zjunlp/LightMem-Ego.

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Paper submitter about 17 hours ago

LightMem-Ego: Bringing lifelong memory to AI assistants on smartphones and AI glasses, enabling them to see, remember, and help with your daily life.

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