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arXiv · 2505.23058

Be.FM: Open Foundation Models for Human Behavior

Yutong Xie·Zhuoheng Li·Xiyuan Wang·Yijun Pan·Qijia Liu·Xingzhi Cui·Kuang-Yu Lo·Ruoyi Gao·Xingjian Zhang·Jin Huang·Walter Yuan·Matthew O. Jackson·Qiaozhu Mei
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Abstract

Despite their success in numerous fields, the potential of foundation models for modeling and understanding human behavior remains largely unexplored. We introduce Be.FM, one of the first open foundation models designed for human behavior modeling. Built upon open-source large language models and fine-tuned on a diverse range of behavioral data, Be.FM can be used to understand and predict human decision-making. We construct a comprehensive set of benchmark tasks for testing the capabilities of behavioral foundation models. Our results demonstrate that Be.FM can predict behaviors, infer characteristics of individuals and populations, generate insights about contexts, and apply behavioral science knowledge.

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Yutong Xie, Zhuoheng Li, Xiyuan Wang, Yijun Pan, Qijia Liu, Xingzhi Cui, Kuang-Yu Lo, Ruoyi Gao, Xingjian Zhang, Jin Huang, Walter Yuan, Matthew O. Jackson, Qiaozhu Mei. 2025-05-29. Be.FM: Open Foundation Models for Human Behavior. https://arxiv.org/abs/2505.23058

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