Zhou et al. 2026 — localized memory update and search beat global reorganization on cost-utility, until long-context workloads flip the trade

From an ablation across 12 memory architectures and 5 benchmark workloads, the paper's "Operational Scaling Rule": "Localized update and search yield the strongest cost–utility balance." Richer global-reorganization systems (named: Cognee, MemoryOS, Zep) pay off only when their upkeep avoids broad recomputation — "otherwise overhead offsets its gains" — and the trade reverses under long-context workloads, where "whole-memory coordination becomes the dominant cost driver."

Latency detail carried honestly: figures relayed at capture level (LightMem ~3.7s vs Cognee ~116s / Zep ~155s per operation) came from an AI-summarized read of Figure 11, not extracted text — directional (order-of-magnitude gap favoring localized systems), not citable numbers. [unverified-quant].

Why the vault keeps this. It is general, external evidence for the vault's targeted-plus-periodic bet: forward-hooks + lint are "localized update"; a Dreams-style pass (claim-anthropic-dreams-nondestructive-reorg) is "whole-memory coordination." The first vault-lint's catch-count (31 hygiene / 0 truth-defects at n=63) points the same way — question-consolidation-pass-vs-revisit-protocol holds both pieces of evidence and stays open. The paper's own caveat transfers as a watch condition: the vault's coming embedding layer (question-embedding-layer-threshold-crossed) increases retrieval load per query, which is a step toward the workload regime where the paper says the trade begins to reverse. moc-peer-field-agent-memory.