English(EN) REM: What to Store, When to Recall, What to Forget in Experience Memory for Coding Agents

新的REM框架增强了LLM代理在编码任务中的记忆能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-21 04:00

研究人员开发了一个名为REM（可重用经验记忆）的新框架，旨在增强大型语言模型（LLM）代理的记忆能力。REM通过将存储、回忆和遗忘的决策直接整合到代理的思考-行动循环中，来管理整个记忆生命周期。这种方法在准确检索相关轨迹和提高代码库级别错误修复任务的最终任务解决率方面，比现有的记忆系统更有效，同时还降低了成本。 AI

影响该框架有望提高LLM代理在软件开发等复杂、长周期的任务中的效率和有效性。

排序理由该集群包含一篇详细介绍LLM代理新框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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Newsworthiness bucket: Tool; 该集群包含一篇详细介绍LLM代理新框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Xinyi Lisa Chen, Pedro Herrero-Vidal, Xiaohan Chen, Xiaojing Yu, Cris Liu, Bingqing Song, Bin Xu, Suleiman A. Khan, You-Lin Chen · 2026-10-21 04:00

REM：编码代理在经验记忆中存储什么、何时回忆、何时遗忘

arXiv:2610.27377v1 Announce Type: new Abstract: Large language model (LLM) agents now autonomously complete long-horizon tasks, such as repository-level coding, through hundreds of think-act steps, yet the experience each run produces is rarely reused on the next. Prior memory sy…

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报道来源 [1]

REM：编码代理在经验记忆中存储什么、何时回忆、何时遗忘

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