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arXiv AI By Miao Su, Yucan Guo, Zixuan Li, Long Bai, Zhongni Hou, Xiaolong Jin, Jiafeng Guo

MemScope: Evolving Agent Memory Architectures through Localized Code Repair

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MemScope introduces a framework for evolving large language model (LLM) agent memory architectures by using localized code repair guided by detailed execution traces and runtime memory states. The Patch Agent identifies precise repair targets and applies bounded, in-place edits while respecting provider identity and memory compatibility constraints. Experiments on GAIA, xBench, and ALFWorld show that MemScope improves accuracy and correct answer rates, achieving higher success rates with a modest median code‑change ratio of 4.4%.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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