HyperOS-Mem: OS-Centric Personal Memory via Fast–Slow Hierarchical Event Graph

Existing personal memory systems and benchmarks predominantly focus on isolated interaction domains (e.g., dialogue or video), yielding memories that capture only partial slices of user activity trajectories. By contrast, users leave massive cross-app, cross-modal, and cross-temporal digital trajectories on Smartphone OS, such as the scattered conversations, orders, locations, and screens generated throughout a business trip. While building an OS-centric personal memory is highly promising, it faces three critical challenges: (1) fragment integration, as heterogeneous observations lack a unified structure; (2) event decoupling, given that parallel event logs intertwine chronologically; and (3) immediate attribution, because event membership and hierarchical context often require later evidence to resolve.To systematically study this problem, we construct PMM-Bench, comprising 3.83 million system-level records from 20 users, encompassing eight daily scenarios and featuring five representative evaluation settings. We further propose HyperOS-Mem, which organizes atomic observations into an evidence-grounded, temporally evolving, event-centric hierarchical memory graph through a coordinated fast–slow process.Experiments on PMM-Bench demonstrate that existing memory systems remain limited in this OS-level setting, whereas HyperOS-Mem achieves SOTA performance, validating the effectiveness of the event-centric memory paradigm.