标题： 基于视觉信息和预测导向提示的基于大语言模型的身体世界模型 显示英文标题

标题： The Embodied World Model Based on LLM with Visual Information and Prediction-Oriented Prompts

摘要： 近年来，随着机器学习，特别是视觉和语言理解方面的进步，嵌入式人工智能的研究也得到了发展。 VOYAGER 是一个著名的基于大语言模型的具身人工智能，它能够在我的世界（Minecraft）中实现自主探索，但它存在视觉数据利用不足和作为世界模型功能有限等问题。 在本研究中，旨在提高具身人工智能性能的情况下，探讨了利用视觉数据以及大语言模型作为世界模型的功能的可能性。 实验结果表明，大语言模型能够从视觉数据中提取必要信息，而信息的利用提高了其作为世界模型的性能。 还建议设计的提示可以发挥大语言模型作为世界模型的功能。 显示英文摘要

摘要： In recent years, as machine learning, particularly for vision and language understanding, has been improved, research in embedded AI has also evolved. VOYAGER is a well-known LLM-based embodied AI that enables autonomous exploration in the Minecraft world, but it has issues such as underutilization of visual data and insufficient functionality as a world model. In this research, the possibility of utilizing visual data and the function of LLM as a world model were investigated with the aim of improving the performance of embodied AI. The experimental results revealed that LLM can extract necessary information from visual data, and the utilization of the information improves its performance as a world model. It was also suggested that devised prompts could bring out the LLM's function as a world model.