SOURCE-LINKED INTELLIGENCE
PolyMemDB: A Polyglot Database System for AI Memory Management
With the widespread adoption of personal intelligent agents, users generate massive, heterogeneous data during long-term interactions. Leveraging this data as long-term memory helps reduce token overhead and deliver personalized experiences. However, existing memory systems face two primary limitations: they rely on single-storage paradigms that fragment multi-dimensional data, and they lack fine-grained data provenance to resolve long-term factual conflicts, thereby worsening LLM hallucinations. In this demonstration, we introduce PolyMemDB, a novel system tailored for managing agent memory.
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-26T09:38:02.000Z
First collected: 2026-09-21T09:22:01.459Z. This is not the publication date.