Unipa-GPT：面向意大利语大学场景问答的大型语言模型
Unipa-GPT: Large Language Models for university-oriented QA in Italian
AI总结：
本文介绍了面向巴勒莫大学课程咨询的聊天机器人 Unipa-GPT，基于 gpt-3.5-turbo，结合 RAG 与微调方法构建，并在 SHARPER night 活动中验证了其性能。
摘要：
本文阐述了 Unipa-GPT 的架构与训练过程。Unipa-GPT 是一个基于大型语言模型的聊天机器人，旨在帮助学生在巴勒莫大学选择学士或硕士学位课程。Unipa-GPT 基于 gpt-3.5-turbo，并在欧洲研究者之夜（SHARPER night）活动中展示。在实验中，我们同时采用了检索增强生成（RAG）方法和微调方法来开发该系统。本文展示了 Unipa-GPT 的整体架构，对 RAG 系统和微调系统进行了比较，并简要讨论了它们的性能。此外，还展示了与其他大型语言模型的进一步比较以及在 SHARPER night 期间的实验结果。语料库和代码已在 GitHub 上公开。
英文摘要：
This paper illustrates the architecture and training of Unipa-GPT, a chatbot relying on a Large Language Model, developed for assisting students in choosing a bachelor/master degree course at the University of Palermo. Unipa-GPT relies on gpt-3.5-turbo, it was presented in the context of the European Researchers' Night (SHARPER night). In our experiments we adopted both the Retrieval Augmented Generation (RAG) approach and fine-tuning to develop the system. The whole architecture of Unipa-GPT is presented, both the RAG and the fine-tuned systems are compared, and a brief discussion on their performance is reported. Further comparison with other Large Language Models and the experimental results during the SHARPER night are illustrated. Corpora and code are available on GitHub
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。
