MemArena: An Ego-Centric Benchmark for On-Device Agentic Personal Memory Assistants at Scale

Excerpt

arXiv:2608.02613v2 Announce Type: replace-cross Abstract: Edge-deployed personal memory assistants must handle private interpersonal conversations on-device with open-weight models. Yet, existing memory benchmarks often under-test the combination of activity-dense interaction, ego-centric perspective, and coherent multi-session worlds. MemArena fills these gaps with a single-world conversational benchmark built with its MASim agent simulator, for 50 agents over 15 days (10.3M dialog-text tokens,