标题： 大型语言模型在开放式问题解决方案实现生成中的应用概述与讨论 显示英文标题

标题： An Overview and Discussion on Using Large Language Models for Implementation Generation of Solutions to Open-Ended Problems

摘要： 大型语言模型为设计自动化实现生成方法提供了新的机会，这些方法可以解决超越传统方法的问题求解活动，传统方法需要算法规范，并且只能使用静态领域知识，如性能指标和基本构建块库。 大型语言模型可以支持创建新方法，以支持开放式问题的问题求解活动，例如问题框架设定、探索可能的求解方法、特征详细说明和组合、更高级的实现评估以及处理意外情况。 本报告总结了当前关于大型语言模型的工作，包括模型提示、强化学习和检索增强生成。 也讨论了未来的研究需求。 显示英文摘要

摘要： Large Language Models offer new opportunities to devise automated implementation generation methods that can tackle problem solving activities beyond traditional methods, which require algorithmic specifications and can use only static domain knowledge, like performance metrics and libraries of basic building blocks. Large Language Models could support creating new methods to support problem solving activities for open-ended problems, like problem framing, exploring possible solving approaches, feature elaboration and combination, more advanced implementation assessment, and handling unexpected situations. This report summarized the current work on Large Language Models, including model prompting, Reinforcement Learning, and Retrieval-Augmented Generation. Future research requirements were also discussed.