MemArchitect: A Policy Driven Memory Governance Layer
Persistent Large Language Model (LLM) agents expose a critical governance gap in memory management. Standard Retrieval-Augmented Generation (RAG) frameworks treat memory as passive storage, lacking mechanisms to resolve contradictions, enforce privacy, or prevent outdated information ("zombie memories") from contaminating the context window. We introduce MemArchitect, a governance layer that decouples memory lifecycle management from model weights. MemArchitect enforces explicit, rule-based poli
Record details
Published: 18 March 2026
Source: arXiv
Category: Research
Topics: Regulation · Privacy · Agents & autonomy
Retrieved: 14 July 2026
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ethics.ai (18 March 2026), “MemArchitect: A Policy Driven Memory Governance Layer,” evidence record 7043, https://ethics.ai/record/7043 (originally published by arXiv).
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