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论文精选 65arXiv

RunningTab: Direct Workspace Interaction with Environment-Side Tabs

Much knowledge work produces new deliverables from files a workspace already holds, and LLM agents are beginning to take such work over. Through direct corpus interaction, an agent can search and read any of those files from a terminal with no indexing, and producing a deliverable from many of them in this way is what we call direct workspace interaction (DWI). Reaching the files, however, is only half the task: nothing keeps track of what the task asks for, what has been read, and what was listed but never opened, all of which slip through the context window without leaving a trace, so an agent may extract a figure and still deliver a report without it. To address this, we present RunningTab, a framework that equips direct workspace interaction with an environment-side tab: a per-task rec

AI 解读论文

通过环境侧标签增强直接工作区交互的框架,提升LLM代理的工作效率与可追溯性。

核心方法
引入RunningTab框架,在LLM代理的工作环境中添加环境侧标签,用于记录任务需求、已读文件及未打开文件列表,确保信息可追溯。
适合谁读
研究者、工程师
要解决的问题
现有LLM代理在处理直接工作区交互任务时,缺乏有效的文件追踪与任务管理能力。
关键实验
未提供
主要贡献
提供了一种增强LLM代理直接工作区交互功能的新方法,提高任务完成的质量和效率。
意义与局限
通过解决信息管理问题,RunningTab有助于提高LLM代理处理复杂任务的能力,但也可能面临性能和隐私方面的挑战。
领域:cs.AI作者:Jinheon Baek、Soyeong Jeong、Yumin Choi
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Control evaluations measure whether safeguards can prevent an AI model from causing undesi…

领域:cs.AI作者:Jeffrey Olmo、David Zhang、Tyler Tracy
📎 arXiv🕒 10-23 01:26🔗 arxiv.org

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