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English(EN) Glasseek: A Transparent Recipe for Training and Trustworthy Evaluation of DeepSearch Agents

Glasseek框架增强了深度搜索代理的透明度和性能

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出Glasseek，一个旨在增强深度搜索代理训练的透明度和可复现性的新框架。该框架解决了数据审计、上下文压缩不匹配和评估污染等挑战。Glasseek包括一个可验证的轨迹策管线、一种Compaction-Managed GSPO (CM-GSPO)训练方法以及一个用于评估的模块化防泄露插件。使用Glasseek训练的9B代理在开放权重代理中展示了最先进的性能，并在各种深度研究基准测试中超越了专有代理。 AI

影响 为开放权重代理设定了新的最先进水平，并提高了深度搜索能力评估的严谨性。

排序理由 该集群描述了一篇关于训练AI代理的框架和方法论的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Glasseek框架增强了深度搜索代理的透明度和性能

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该集群描述了一篇关于训练AI代理的框架和方法论的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Cong Pang, Jiaqi Su, Chengrui Wu, Kuihao Yan, Tianrui Zhang, Zixuan Qiu, Chao Lin, Zixiu Lin, Zixuan Chen, Zelin Xiao, Tiankuo Yao, Jiawei Hong, Zixuan Chen, Dan Xu, Lewei Lu, Wenjie Wang, Xin Lou ·

    Glasseek：用于训练和可信评估DeepSearch代理的透明配方

    arXiv:2610.16998v1 Announce Type: new Abstract: Deep search enables language agents to solve complex information-seeking tasks through iterative web exploration. However, developing robust open-source agents remains challenging for three reasons. First, opaque trajectory-construc…

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