evaf

This paper introduces the concept of memory depth for long-running language agents, distinguishing it from retrieval-based memory access, and proposes EVAF, a selective parametric consolidation mechanism using surprise- and valence-gated LoRA updates. Experiments across multiple models show EVAF improves goal persistence after context unload with minimal parametric writes.