ADAIO系统参加BEA-2023教育对话中AI教师回复生成共享任务
The ADAIO System at the BEA-2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues
AI总结：
该研究提出ADAIO参赛系统，利用OpenAI GPT-3评估基线并设计提示，以text-davinci-003的少样本提示方法在BEA-2023共享任务中获得第二名。
摘要：
本文介绍了ADAIO团队在Building Educational Applications（BEA）2023“教育对话中AI教师回复生成”共享任务中的参赛系统。该任务旨在评估最先进的生成模型作为AI教师在师生对话中生成合适回复的性能。我们的系统包括使用OpenAI GPT-3评估多种基线模型，并设计多样化提示来引导OpenAI模型生成教师回复。挑战赛结束后，我们的系统通过在OpenAI text-davinci-003模型上采用基于少样本提示的方法获得第二名。结果凸显了大型语言模型（尤其是OpenAI的GPT-3）在扮演AI教师角色时的少样本学习能力。
英文摘要：
This paper presents the ADAIO team's system entry in the Building Educational Applications (BEA) 2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues. The task aims to assess the performance of state-of-the-art generative models as AI teachers in producing suitable responses within a student-teacher dialogue. Our system comprises evaluating various baseline models using OpenAI GPT-3 and designing diverse prompts to prompt the OpenAI models for teacher response generation. After the challenge, our system achieved second place by employing a few-shot prompt-based approach with the OpenAI text-davinci-003 model. The results highlight the few-shot learning capabilities of large-language models, particularly OpenAI's GPT-3, in the role of AI teachers.
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。
