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arXiv · 2406.17553

Retrieval-Augmented Code Generation for Situated Action Generation: A Case Study on Minecraft

Chalamalasetti Kranti·Sherzod Hakimov·David Schlangen
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Abstract

In the Minecraft Collaborative Building Task, two players collaborate: an Architect (A) provides instructions to a Builder (B) to assemble a specified structure using 3D blocks. In this work, we investigate the use of large language models (LLMs) to predict the sequence of actions taken by the Builder. Leveraging LLMs' in-context learning abilities, we use few-shot prompting techniques, that significantly improve performance over baseline methods. Additionally, we present a detailed analysis of the gaps in performance for future work

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Chalamalasetti Kranti, Sherzod Hakimov, David Schlangen. 2024-06-25. Retrieval-Augmented Code Generation for Situated Action Generation: A Case Study on Minecraft. https://arxiv.org/abs/2406.17553

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