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English(EN) Iris: Climbing to the Search Frontier

Iris搜索代理在网络基准测试中取得SOTA开源成果 · 跟踪2个来源

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了两个大规模搜索代理Iris-mini和Iris-pro，分别拥有350亿和3970亿参数。这些代理利用新颖的数据管道和训练方法，将监督微调与实时搜索的强化学习相结合。在BrowseComp和DeepSearchQA等复杂的网络基准测试中，这些模型在开源搜索代理中取得了最先进（SOTA）的成果，尤其是在采用高级上下文管理技术时。 AI

影响 为开源搜索代理设定了新的SOTA，可能影响未来的网络导航和信息检索技术。

排序理由 该集群描述了一篇详细介绍新AI模型及其在基准测试中表现的研究论文。

在 Hugging Face Daily Papers 阅读 →

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Iris搜索代理在网络基准测试中取得SOTA开源成果 · 跟踪2个来源

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该集群描述了一篇详细介绍新AI模型及其在基准测试中表现的研究论文。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Ziyuan Liu, Hengqi Liu, Zichuan Wang, Yang Qin, Jiachen Liang, Xu Chu, Shaowei Chen, Yuantao Gu, Mu Chuan ·

    Iris：攀登搜索前沿

    arXiv:2609.04304v1 Announce Type: new Abstract: We present Iris-mini and Iris-pro, two search agents trained at the 35B-A3B and 397B-A17B scales, together with the data pipeline and training recipe behind them. Tasks are reverse-constructed from the hyperlink structure of a web c…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Iris：攀登搜索前沿

    Two large-scale search agents are trained via a multi-stage pipeline combining supervised fine-tuning and reinforcement learning against live search, achieving state-of-the-art open-source results on complex web benchmarks through rigorous trajectory filtering and inference-time …

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