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Personalized memory gating unlocks more relevant long-term recall by learning from individual user interaction patterns, outperforming generic policies.
A novel two-axis framework unifies the study of multimodal agent memory, revealing distinct tiers of memory adaptation from static reuse to self-evolving policies.
Mimir achieves an impressive 86.0% success rate on long-horizon tasks, outperforming leading closed-source models by a significant margin.