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CraftAssist: A Framework for Dialogue-enabled Interactive Agents
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This paper describes an implementation of a bot assistant in Minecraft, and the tools and platform allowing players to interact with the bot and to record those interactions. The purpose of building such an assistant is to facilitate the study of agents that can complete tasks specified by dialogue, and eventually, to learn from dialogue interactions.
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Forward citations
Cited by 2 Pith papers
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Evaluating Generative Models as Interactive Emergent Representations of Human-Like Collaborative Behavior
LLM agents in a collaborative 2D game exhibit emergent behaviors such as perspective-taking, theory of mind, and clarification, detected by LLM judges and rated positively by human participants.
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Evaluating Generative Models as Interactive Emergent Representations of Human-Like Collaborative Behavior
Embodied LLM agents exhibit emergent collaborative behaviors indicating mental models of partners in a color-matching game, detected via LLM judges and supported by positive user feedback.
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