Unimib Assistant：为学生需求设计基于RAG的友好型聊天机器人
Unimib Assistant: designing a student-friendly RAG-based chatbot for all their needs
AI总结：
本研究通过基于OpenAI自定义GPTs的RAG系统定制ChatGPT行为，开发Unimib Assistant聊天机器人以满足米兰比可卡大学学生需求，经测试发现其有用户友好等优点，但存在信息不准确等问题，计划进一步完善。
摘要：
大型语言模型（LLMs）的自然语言处理能力前所未有，在不同任务中得到广泛传播和应用。本试点研究聚焦于通过使用OpenAI自定义GPTs功能的检索增强生成（RAG）系统来定制ChatGPT行为。我们的聊天机器人名为Unimib Assistant，旨在通过问答方式为米兰比可卡大学（Unimib）学生的特定需求提供信息和解决方案。我们为系统提供了突出其特定目的和行为的提示词，以及从初始需求发现阶段（采访6名学生）获取的大学相关文档和链接。初步定制阶段后，我们对另外6名学生进行了定性可用性测试，以识别聊天机器人的优缺点，目标是在后续重新设计阶段对其进行改进。虽然聊天机器人因其用户友好的体验、感知到的总体可靠性、结构良好的回复和对话语气而受到赞赏，但也出现了一些显著的技术和功能限制。特别是，系统无法始终提供完全准确的信息，影响了用户的满意度和整体体验。此外，即使上传的材料和给定的提示词中存在相关信息，它也经常忽略报告这些信息。再者，它有时会生成无法点击的链接，破坏了其可信度，因为提供信息来源对我们的用户来说是一个重要方面。我们计划进行进一步深入研究和收集其他用户的反馈，以及实施迭代来完善Unimib Assistant。
英文摘要：
Natural language processing skills of Large Language Models (LLMs) are unprecedented, having wide diffusion and application in different tasks. This pilot study focuses on specializing ChatGPT behavior through a Retrieval-Augmented Generation (RAG) system using the OpenAI custom GPTs feature. The purpose of our chatbot, called Unimib Assistant, is to provide information and solutions to the specific needs of University of Milano-Bicocca (Unimib) students through a question-answering approach. We provided the system with a prompt highlighting its specific purpose and behavior, as well as university-related documents and links obtained from an initial need-finding phase, interviewing six students. After a preliminary customization phase, a qualitative usability test was conducted with six other students to identify the strengths and weaknesses of the chatbot, with the goal of improving it in a subsequent redesign phase. While the chatbot was appreciated for its user-friendly experience, perceived general reliability, well-structured responses, and conversational tone, several significant technical and functional limitations emerged. In particular, the satisfaction and overall experience of the users was impaired by the system's inability to always provide fully accurate information. Moreover, it would often neglect to report relevant information even if present in the materials uploaded and prompt given. Furthermore, it sometimes generated unclickable links, undermining its trustworthiness, since providing the source of information was an important aspect for our users. Further in-depth studies and feedback from other users as well as implementation iterations are planned to refine our Unimib Assistant.
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。
