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
AI 导读
PolyMemDB 是一个为智能体记忆管理设计的新型系统，采用多语言存储架构，支持图、向量、概率及时空等多种记忆类型。其概率推理引擎结合时间衰减与半环聚合，可解决长期事实冲突、提供细粒度数据溯源，并让用户透明追踪推理链，从而降低 LLM 幻觉和 token 开销。该工作已在 arXiv 上作为演示系统发布。
正文 · 原文
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