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English(EN) ScaffoldAgent: Utility-Guided Dynamic Outline Optimization for Open-Ended Deep Research

ScaffoldAgent框架动态优化研究大纲

研究人员推出ScaffoldAgent,一个旨在通过动态优化报告大纲来增强开放式深度研究的新框架。该系统采用效用引导反馈机制,通过扩展、收缩和修订操作来管理大纲演变。在DeepResearch Bench和DeepResearch Gym上的实验表明,与现有的深度研究代理相比,ScaffoldAgent提高了长篇报告生成和事实依据的准确性。 AI

影响 通过提高报告生成和事实准确性,增强AI在复杂研究任务中的能力。

排序理由 该集群包含一篇详细介绍AI辅助研究新框架的研究论文。

在 arXiv cs.MA (Multiagent) 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

ScaffoldAgent框架动态优化研究大纲

报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Zhibang Yang, Xinke Jiang, Yuzhen Xiao, Ruizhe Zhang, Yue Fang, XinFei Wan, Zhengxing Song, Yuxuan Liu, Yuheng Huang, Xu Chu, Junfeng Zhao, Yasha Wang ·

    ScaffoldAgent:开放式深度研究的实用性引导动态大纲优化

    arXiv:2606.20122v1 Announce Type: new Abstract: Open-ended deep research (OEDR) requires systems to acquire knowledge through multi-round retrieval and generate coherent long-form reports. The outline plays a central role as a structural scaffold that coordinates retrieval, evide…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Yasha Wang ·

    ScaffoldAgent:开放式深度研究的实用性引导动态大纲优化

    Open-ended deep research (OEDR) requires systems to acquire knowledge through multi-round retrieval and generate coherent long-form reports. The outline plays a central role as a structural scaffold that coordinates retrieval, evidence organization, and generation. However, exist…