用少量示例提示让大模型自动改工业自动化代码，保护数据还能省事。
Utilizing LLMs for Industrial Process Automation: A Case Study on Modifying RAPID Programs
- 用少样本提示法直接操作专有工业编程语言，无需定制训练。
- 在本地部署即可完成简单代码修改，保障企业数据安全。
- 适合不想投入大量资源但需自动化工业程序的企业。
近年来大量研究探讨了大型语言模型（LLMs）在软件工程中的应用，但多数聚焦于通用编程语言。针对工业过程自动化领域中使用高度专用、通常仅限于专有环境的编程语言，其应用仍缺乏探索。本文研究企业在不投入大量精力进行领域特定语言模型训练的情况下，如何利用现有 LLM 实现自动化。结果表明，采用少样本提示方法足以解决该语言中简单问题，且可在本地部署执行，从而确保敏感公司数据的安全性。
原文摘要 · Abstract (English)
How to best use Large Language Models (LLMs) for software engineering is covered in many publications in recent years. However, most of this work focuses on widely-used general purpose programming languages. The utility of LLMs for software within the industrial process automation domain, with highly-specialized languages that are typically only used in proprietary contexts, is still underexplored. Within this paper, we study enterprises can achieve on their own without investing large amounts of effort into the training of models specific to the domain-specific languages that are used. We show that few-shot prompting approaches are sufficient to solve simple problems in a language that is otherwise not well-supported by an LLM and that is possible on-premise, thereby ensuring the protection of sensitive company data.
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