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English(EN) Should I Be Polite to My LLM Relevance Judge? Tone as a Severity Operating-Point Shift

研究发现，礼貌的提示会改变大型语言模型的相关性判断

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新发表在arXiv上的研究调查了提示中的礼貌用语对用作相关性判断器的大型语言模型的影响。研究人员发现，语气显著影响模型的判断，并且影响因模型而异。当语气影响一致性时，它似乎会转移模型整体评分的宽松度，而不是提高判断的准确性。研究表明，当精确的相关性标签至关重要时，提示语气可能构成有效性威胁。 AI

影响 凸显了基于大型语言模型的评估指标中潜在的有效性威胁，影响了人工智能生成的相关性判断的可靠性。

排序理由 关于大型语言模型行为的学术论文。[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 →

研究发现，礼貌的提示会改变大型语言模型的相关性判断

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关于大型语言模型行为的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Meng Li ·

    我应该对我的LLM相关性评判者保持礼貌吗？语气作为严重性操作点转移

    Large language models are increasingly used as relevance judges, yet their labels can shift with prompt surface form. We study one such feature -- tone -- on 3,498 TREC DL19/DL20 query-passage pairs, across eight judge models, five classifier-calibrated politeness levels, and thr…

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