A Heterogeneous Temporal Memory Governance Framework for Long-Term LLM Persona Consistency

📰 ArXiv cs.AI

arXiv:2605.14802v1 Announce Type: new Abstract: Large language models often suffer from fact loss, timeline confusion, persona drift, and reduced stability during long-range interaction, especially under high-noise knowledge bases, context clearing, and cross-model transfer. To address these issues, we introduce ARPM, an external temporal memory governance framework for long-term dialogue. ARPM separates static knowledge memory from dynamic dialogue experience memory and combines vector retrieva

Published 16 May 2026
Read full paper → ← Back to Reads