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English(EN) Are These Modules Worth Their Cost? A Paradigm-Level Accuracy-Cost Analysis of In-context Learning Text-to-SQL

研究分析文本到SQL的上下文内学习模块的成本效益

一篇新的研究论文分析了文本到SQL任务的上下文内学习(ICL)管道中不同模块的成本效益。该研究在五个经常出现的模块上实现了17种配置,评估了它们在各种骨干上的边际准确性贡献和相关成本。研究结果表明,执行反馈细化在低成本下始终是有益的,而其他模块则表现出依赖于骨干的性能。研究表明,使用中等层级的骨干优化管道结构可能比使用具有基本管道的前沿模型更有效,为配置提供了成本意识的指导。 AI

影响 为优化文本到SQL管道提供了可操作的指导,有可能提高AI应用程序的效率和准确性。

排序理由 该集群包含一篇发表在arXiv上的学术论文,详细介绍了研究结果。[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 →

研究分析文本到SQL的上下文内学习模块的成本效益

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该集群包含一篇发表在arXiv上的学术论文,详细介绍了研究结果。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Jiayan Lin, Yujia Liu, Zijin Hong, Zheng Yuan, Yilin Xiao, Hao Chen, Qinggang Zhang, Xiao Huang, Feiran Huang ·

    这些模块是否物有所值?上下文学习文本到SQL的范式级准确性-成本分析

    arXiv:2608.28432v1 Announce Type: new Abstract: Recent advances in in-context learning (ICL) text-to-SQL have substantially improved execution accuracy on public benchmarks by assembling increasingly elaborate pipelines around the base generator, yet existing studies typically re…