What Should an Agent Remember? Disentangling Retention from Retrieval in Bounded-Memory Evaluation

arXiv cs.AIOctober 2, 2026en

arXiv:2610.00366v1 Announce Type: new Abstract: A persistent agent must decide both what to retain as information arrives and what to surface once a query appears, yet memory evaluations can confound these decisions by comparing methods that differ in both retention and selection. We build a streaming-recall benchmark crossing retention and selection rules and evaluate every condition on the same 300 seeded episodes. Holding access fixed, query-aware selection improves required-fact recall by 15.5 percentage points (95% CI: 12.8 to 18.2), whereas a mixed comparison that also changes history access reports a 68.7-point advantage, of which 53.2 points are attributable to access. Under bounded

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