Despite their success in numerous fields, the potential of foundation models for modeling and understanding human behavior remains largely unexplored. We introducethis http URL, 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,this http URLcan 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 thatthis http URLcan predict behaviors, infer characteristics of individuals and populations, generate insights about contexts, and apply behavioral science knowledge.
View on arXiv@article{xie2025_2505.23058,
title={ Be.FM: Open Foundation Models for Human Behavior },
author={ Yutong Xie and Zhuoheng Li and Xiyuan Wang and Yijun Pan and Qijia Liu and Xingzhi Cui and Kuang-Yu Lo and Ruoyi Gao and Xingjian Zhang and Jin Huang and Walter Yuan and Matthew O. Jackson and Qiaozhu Mei },
journal={arXiv preprint arXiv:2505.23058},
year={ 2025 }
}