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English(EN) ReasonSTL: Bridging Natural Language and Signal Temporal Logic via Tool-Augmented Process-Rewarded Learning

ReasonSTL框架通过开源LLM将自然语言转换为形式逻辑

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了ReasonSTL，一个旨在将自然语言需求转换为信号时序逻辑（STL）公式的新型框架。这种工具增强的方法利用本地开源语言模型进行翻译，解决了与商业LLM API相关的成本和隐私问题。ReasonSTL将过程分解为推理、工具调用和公式构建，并结合了进程奖励训练和一个名为STL-Bench的新基准。 AI

影响 提供了一种保护隐私、低成本的方法来生成形式化规范，有可能改进自主和网络物理系统的验证。

排序理由 这是一篇研究论文，详细介绍了一个将自然语言转换为信号时序逻辑的新框架和基准。

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ReasonSTL框架通过开源LLM将自然语言转换为形式逻辑

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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Bowen Ye, Zhijian Li, Junyue Huang, Junkai Ma, Xiang Yin ·

    ReasonSTL：通过工具增强的进程奖励学习连接自然语言和信号时序逻辑

    arXiv:2605.06483v1 Announce Type: new Abstract: Signal Temporal Logic (STL) is an expressive formal language for specifying spatio-temporal requirements over real-valued, real-time signals. It has been widely used for the verification and synthesis of autonomous systems and cyber…

  2. arXiv cs.AI TIER_1 English(EN) · Xiang Yin ·

    ReasonSTL：通过工具增强的进程奖励学习连接自然语言和信号时序逻辑

    Signal Temporal Logic (STL) is an expressive formal language for specifying spatio-temporal requirements over real-valued, real-time signals. It has been widely used for the verification and synthesis of autonomous systems and cyber-physical systems. In practice, however, users o…

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