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arXiv cs.AI· Yu Wang, Jiaheng Lu·· 12 小时前AI 评分34

PolyMemDB:面向 AI 记忆管理的多语言数据库系统

PolyMemDB: A Polyglot Database System for AI Memory Management

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PolyMemDB 是一个专为智能体记忆管理设计的多语言数据库系统,采用多存储架构统一管理图、向量、概率和时空等多类记忆数据。它内置概率推理引擎,结合时间衰减与半环聚合来消解长期事实冲突,并提供细粒度数据溯源以支持透明追踪推理链,从而缓解 LLM 幻觉。

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Abstract: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. PolyMemDB has a polyglot storage architecture designed to track and manage various memory types, including graph, vector, probability and spatial-temporal data. To ensure factual consistency and reduce hallucinations, it features a probabilistic inference engine that integrates temporal decay with semiring aggregation, resolving long-term factual conflicts, providing detailed data provenance, and enabling users to trace reasoning chains transparently.
Subjects: Databases (cs.DB); Artificial Intelligence (cs.AI)
Cite as: arXiv:2608.25577 [cs.DB]
  (or arXiv:2608.25577v2 [cs.DB] for this version)
  https://doi.org/10.48550/arXiv.2608.25577

arXiv-issued DOI via DataCite

Submission history

From: Yu Wang [view email]
[v1] Wed, 26 Aug 2026 09:38:02 UTC (3,933 KB)
[v2] Thu, 22 Oct 2026 18:19:38 UTC (3,916 KB)

来源:arXiv cs.AI · arxiv.org