MobileMem: Learning from a Year of Mobile Experiences
3.20T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2608.13606.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryMobileMem is a benchmark and framework for evaluating on-device long-term memory in personal AI agents, built from a year-scale collection of synthesized mobile user-app sessions. It covers text and multimodal tasks including multi-hop reasoning, temporal reasoning, knowledge updating, and implicit preference inference.
Why it mattersProposes a year-scale benchmark for personal AI agent memory grounded in realistic mobile sessions, relevant to researchers building continuous-learning assistants.
Cited by
No citations on record.