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arXiv AI By Olukunle Owolabi, Pulkit Gupta, Fei Wang

When to Remember, When to Abstain: Category-Conditioned Retention for Reliable Agent Memory

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The paper proposes a category‑conditioned retention strategy for agent memory, arguing that a single global confidence threshold is insufficient to balance reliability across different assertion types. By applying stricter retention bars to value assertions while allowing more liberal retention for other categories, the authors demonstrate a 36% relative reduction in unsupported value claims and a 13‑percentage‑point increase in coverage compared to a global threshold. The study is evaluated on a cold‑start memory pipeline with 100 synthetic personas, showing that selective, category‑aware retention improves overall memory reliability.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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