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English(EN) MARS: Training Multilingual Search Agents for Retriever-Free Evidence Acquisition

新的MARS代理通过shell命令实现无检索的多语言搜索

研究人员开发了MARS,一种新颖的多语言搜索代理,旨在通过可执行的shell命令直接与原始语料库进行交互,从而绕过传统检索系统的需求。这种直接语料库交互(DCI)的方法旨在克服现有的多语言检索增强生成方法存在的跨语言错误和索引复杂性等局限性。MARS采用语料库原生实体接地来确保可靠的证据检索,并通过冗余感知奖励机制来通过强化学习优化搜索轨迹,展示了强大的跨语言泛化能力和减少的冗余交互。 AI

影响 这项研究通过实现直接语料库交互,可能带来更高效、更准确的多语言信息检索系统。

排序理由 该集群描述了一篇研究论文,其中详细介绍了一种用于多语言搜索代理的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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

新的MARS代理通过shell命令实现无检索的多语言搜索

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Signal score
17 / 100
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Newsworthiness bucket
Tool
该集群描述了一篇研究论文,其中详细介绍了一种用于多语言搜索代理的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, other
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High
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Breaking (< 6h)
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Rui Qi, Yunlong Liang, Yufeng Chen, Jinan Xu, Fandong Meng, Kaiyu Huang ·

    MARS:训练多语言搜索代理以实现无检索证据获取

    arXiv:2611.09090v1 Announce Type: new Abstract: Existing multilingual retrieval-augmented generation relies heavily on learned retrievers and similarity-based ranking from multilingual collections, which are vulnerable to cross-lingual retrieval errors and indexing overhead. In t…