MenuCraft：基于大型语言模型的交互式菜单系统设计
MenuCraft: Interactive Menu System Design with Large Language Models
AI总结：
本文提出MenuCraft，一个基于大型语言模型的AI辅助交互式菜单设计系统，通过对话协作和上下文学习简化菜单设计并支持定制。
摘要：
用户界面的菜单系统设计是一项具有挑战性的任务，涉及众多设计选项和多种人因因素。例如，设计师需要考虑的一个关键因素是菜单命令之间的语义关系和系统关系。然而，由于可用资源有限，捕捉这些关系可能具有挑战性。大型语言模型在这方面可以提供帮助，利用其预训练知识来设计和优化菜单系统。在本文中，我们提出了MenuCraft，一个AI辅助的菜单设计工具，使设计师能够与对话系统协作来设计菜单。MenuCraft提供了一个基于语言的交互式菜单设计工具，简化了菜单设计过程，并支持对设计选项的轻松定制。MenuCraft通过对话支持多种交互方式，允许进行上下文学习。
英文摘要：
Menu system design for user interfaces is a challenging task involving many design options and various human factors. For example, one crucial factor that designers need to consider is the semantic and systematic relation of menu commands. However, capturing these relations can be challenging due to limited available resources. Large language models can be helpful in this regard, using their pre-training knowledge to design and refine menu systems. In this paper, we propose MenuCraft, an AI-assisted designer for menu design that enables collaboration between the designer and a dialogue system to design menus. MenuCraft offers an interactive language-based menu design tool that simplifies the menu design process and enables easy customization of design options. MenuCraft supports a variety of interactions through dialog that allows performing in-context learning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
