[2603.03290] AriadneMem: Threading the Maze of Lifelong Memory for LLM Agents

Computer Science > Computation and Language arXiv:2603.03290 (cs) [Submitted on 5 Feb 2026] Title:AriadneMem: Threading the Maze of Lifelong Memory for LLM Agents Authors:Wenhui Zhu, Xiwen Chen, Zhipeng Wang, Jingjing Wang, Xuanzhao Dong, Minzhou Huang, Rui Cai, Hejian Sang, Hao Wang, Peijie Qiu, Yueyue Deng, Prayag Tiwari, Brendan Hogan Rappazzo, Yalin Wang View a PDF of the paper titled AriadneMem: Threading the Maze of Lifelong Memory for LLM Agents, by Wenhui Zhu and 13 other authors View PDF HTML (experimental) Abstract:Long-horizon LLM agents require memory systems that remain accurate under fixed context budgets. However, existing systems struggle with two persistent challenges in long-term dialogue: (i) \textbf{disconnected evidence}, where multi-hop answers require linking facts distributed across time, and (ii) \textbf{state updates}, where evolving information (e.g., schedule changes) creates conflicts with older static logs. We propose AriadneMem, a structured memory system that addresses these failure modes via a decoupled two-phase pipeline. In the \textbf{offline construction phase}, AriadneMem employs \emph{entropy-aware gating} to filter noise and low-information message before LLM extraction and applies \emph{conflict-aware coarsening} to merge static duplicates while preserving state transitions as temporal edges. In the \textbf{online reasoning phase}, rather than relying on expensive iterative planning, AriadneMem executes \emph{algorithmic bridge disc...