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English(EN) Self-Refining Prompt Induction for Streaming Text-to-SQL

新方法改进了流式数据的文本到SQL助手

研究人员开发了一种名为自精炼提示归纳法(SRPI)的新方法,用于改进流式引擎的文本到SQL助手。这种离线技术将生成失败转换为可重用的指令,而无需更改模型权重。精炼器模块使用LLM裁判的反馈来修改生成器的提示,然后进行压缩以提高效率。在Confluent Cloud Flink SQL上的评估表明,多个生成器的提示质量得到了显著提高,其中一个系统的得分从85.3%提高到97.5%。 AI

影响 该方法可以提高将自然语言转换为流数据SQL查询的AI助手的准确性和效率。

排序理由 该集群包含一篇详细介绍改进AI模型性能的新方法的论文。[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 →

新方法改进了流式数据的文本到SQL助手

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该集群包含一篇详细介绍改进AI模型性能的新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]
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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) · Gaetano Rossiello, Alfio Gliozzo, Nandana Mihindukulasooriya, Erick Lee, Nabila Siregar, Lisa Amini ·

    用于流式文本到SQL的自修正提示归纳

    arXiv:2611.00960v1 Announce Type: new Abstract: Text-to-SQL assistants for streaming engines must handle dialect-specific types, windowing rules, and temporal semantics, including constructs poorly handled by generic prompts. We present Self-Refining Prompt Induction (SRPI), an o…