用于编程与机器人教育的大语言模型
LLMs for Coding and Robotics Education
AI总结：
本文探讨大语言模型在机器人编程教育中的应用趋势，测试多款模型，发现GPT-4V在代码任务上表现最佳，但生成框图图像仍有不足。
摘要：
大语言模型和多模态大语言模型近期彻底改变了人工智能领域。越来越多的地区正在采用这些先进技术。在此背景下，机器人编程教育日益受到关注。为了教导幼儿如何编程并参与机器人挑战赛，大语言模型被用于机器人代码的解释、生成和修改。本文中，我们强调了机器人编程教育中的一个重要趋势。我们在传统编程任务以及更具挑战性的机器人代码生成任务（包括框图）上测试了多款主流大语言模型。结果表明，GPT-4V在所有测试中均优于其他模型，但在生成框图图像方面存在困难。
英文摘要：
Large language models and multimodal large language models have revolutionized artificial intelligence recently. An increasing number of regions are now embracing these advanced technologies. Within this context, robot coding education is garnering increasing attention. To teach young children how to code and compete in robot challenges, large language models are being utilized for robot code explanation, generation, and modification. In this paper, we highlight an important trend in robot coding education. We test several mainstream large language models on both traditional coding tasks and the more challenging task of robot code generation, which includes block diagrams. Our results show that GPT-4V outperforms other models in all of our tests but struggles with generating block diagram images.
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。
