arXiv:2608.02097cs.AIcs.IR2026-08

让搜索代理先存页再取料,避免重复加载,提升长流程问答准确率。

Fetch-then-Explore: Decoupling Selection from Extraction over a Persistent Workspace for Search Agents

  • 页面选中后持久保存到文件系统,不再随会话丢弃。
  • 在多轮推理中可反复回溯页面,证据获取更完整。
  • 适合需要长期记忆与多次回溯的复杂搜索任务。

搜索代理能处理需数十次搜索才能解答的问题,但其读取网页的方式远未受到足够关注。现有方法多采用两种接口:‘访问即读’在获取时固定阅读内容,无法根据后续需求调整;‘有状态浏览’则按需提取,但仅持有一个页面,换页即释放。导致后期才重要的页面需重新获取和渲染。本文提出‘先取后探’(Fetch-then-Explore),将页面选择与证据提取解耦,将选定页面持久化存储于每问题的工作区文件系统中,而非上下文窗口或临时会话。证据可在后续按需提取,且页面不因切换而释放,支持跨多轮积累信息。在包含固定搜索的统一ReAct框架下,对比片段仅限、访问即读与浏览基线,在BrowseComp和WideSearch两个开放网络基准上测试三种代理模型。结果表明,该方法在所有模型上均显著提升BrowseComp准确率,并在WideSearch上普遍持平或超越基线。行为分析显示,优势源于工作区的核心机制:能多次返回已离开页面,从而弥补初次遗漏的信息。

原文摘要 · Abstract (English)

Search agents now answer questions that take dozens of searches to settle, yet how such an agent reads a page has drawn far less attention than how it finds one. Nearly all of them use one of two document interfaces, and both tie a page to the moment it is opened. \emph{Visit-and-read} injects a reading of the page into the message history at fetch time, fixing that reading before the agent knows which fact it will need. Stateful \emph{browsing} instead extracts on demand from the page in hand, but holds one page at a time and releases it as soon as the agent opens another. Either way, a page that turns out to matter many turns later has to be fetched and rendered into context all over again. We propose \textbf{Fetch-then-Explore}, which separates page selection from evidence extraction and keeps what it selects: pages are recorded in a per-question workspace on the filesystem rather than the context window or a transient session, and evidence is pulled from them on demand later. Selection becomes almost free, extraction can wait until the agent knows what to look for and be repeated as its hypothesis sharpens, and pages are not released when the agent moves on, so evidence accumulates across the trajectory. In a unified ReAct harness with fixed search, we compare Fetch-then-Explore against snippet-only, visit-and-read, and browsing baselines on two open-web benchmarks, BrowseComp and WideSearch, across three agent backbones. It leads BrowseComp accuracy at every backbone and generally matches or exceeds the baselines on WideSearch, and a behavioral analysis traces the gains to the workspace's defining move: returning to a page after leaving it, which it does far more than any transient interface, so evidence missed on a first pass can still be recovered later.

搜索代理知识积累工作区设计

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