Large Language Model Assisted Experiment Design with Generative Human-Behavior Agents

This paper explores the use of Large Language Models (LLMs) to assist in experiment design by creating generative agents that simulate human behavior. This approach enables researchers to pre-test experimental designs before conducting actual human studies.

Authors: H. Liu, Y. Tang, Z. Zhang, Z. Zheng, T. Zhu (in alphabetical order)

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