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English(EN) Search Engines Never Say No: How Frozen Agents React When the Retrieval Tool Refuses

新研究表明,LLM代理通过工具拒绝信号得到改进

一篇新的arXiv论文探讨了当检索工具不提供相关信息时,被称为“冷冻代理”的大型语言模型如何反应。研究人员发现,一个简单的、未宣布的拒绝信号显著提高了Qwen3和Claude Haiku 4.5等模型的弃权率(针对无法回答的问题),从而大大减少了错误答案。研究还强调,拒绝信号的措辞会影响代理行为,解释比纯粹的标记或软警告更有效。 AI

影响 提高代理弃权率可以带来更可靠的AI系统,这些系统能更好地指示何时缺乏信息。

排序理由 该集群包含一篇发表在arXiv上的研究论文,详细介绍了LLM行为的实验结果。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.IR (Information Retrieval) 阅读 →

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

新研究表明,LLM代理通过工具拒绝信号得到改进

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Tool
该集群包含一篇发表在arXiv上的研究论文,详细介绍了LLM行为的实验结果。[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, model release
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
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2 days old
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报道来源 [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Vinoth Selvendran ·

    搜索引擎从不拒绝:检索工具拒绝时,冻结的代理如何反应

    A search tool never says no: it returns its top-k passages even when the index holds no answer, so the agent sees irrelevant text instead of a miss signal. We ask what frozen search agents do when the tool refuses instead. On an index-hole testbed (257 NQ and 300 HotpotQA questio…