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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.
External agent scaffolding can be discarded after training by distilling evolved decision-making procedures directly into a model's native reasoning traces.