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Fortunate Recall: Ontology-Driven Memory Lifecycle Management for Persistent Coherence in LLMs

Paper recorded by Signals 4 on 2026-09-09 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-09 on arXiv · recorded by Signals 4 on 2026-09-10

Category: cs.AI · 人工智能 · first seen 2026-09-10

Abstract

Current LLM memory systems treat all personal facts identically, so stores grow without bound while retrieval precision degrades. The core challenge is lifecycle management: which memories should persist, which should be replaced, and at what rate, conditioned on the behavioral type of each fact. Fortunate Recall (FR) is a composable policy layer that classifies personal facts into a 10+1 behavior

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#128 most recent of 300 cs.AI papers we have recorded · ↑ newer: Emergency Department Revisit Quality Review Screening: Exploring Human · ↓ older: Can Foundation Models Moderate Online Content? Evaluating Instruction-
Cite this page: Fortunate Recall: Ontology-Driven Memory Lifecycle Management for Persistent Coherence in LLMs: the #128 most recent of 300 cs.AI papers we have recorded (as of 2026-09-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/fortunate-recall-ontology-driven-memory-lifecycle-management-for-persistent-cohe.html
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