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English(EN) Does a Governed Confidence Score Know When a Text-to-SQL Answer Is Right? An Exploratory Study on BIRD and a Pre-registered Confirmation on Spider

文本到SQL置信度分数在Spider数据集上显示出更高的准确性

一篇新的研究论文探讨了文本到SQL系统中置信度分数的有效性,特别是评估了GPT-5.1在BIRD和Spider数据集上的表现。研究发现,设计的置信度分数在BIRD上的表现较弱,隐藏了许多正确的答案。然而,在冻结了样本一致性决定分数的规则,并应用确定性检查作为否决后,该系统在Spider上的表现显著提高,AUROC更高,隐藏的正确答案更少。研究表明,将一致性纳入分数的方法对于提高对话式分析的准确性和覆盖率至关重要。 AI

影响 这项研究通过改进置信度分数的生成和利用方式,有望带来更可靠的对话式分析系统。

排序理由 学术论文,详细介绍了对文本到SQL置信度分数的探索性研究。[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 →

文本到SQL置信度分数在Spider数据集上显示出更高的准确性

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学术论文,详细介绍了对文本到SQL置信度分数的探索性研究。[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) · Raghu Venkat, Tricha Anjali ·

    受控置信度分数能否判断 Text-to-SQL 答案是否正确?一项关于 BIRD 的探索性研究和 Spider 的预注册确认

    arXiv:2610.17256v1 Announce Type: new Abstract: Conversational analytics lets people ask questions of records spread across many systems and get answers in plain language; it is useful only if each answer can be trusted and explained. A production system of this kind attaches a c…