Spencer Lynch


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2025

pdf bib
SOTOPIA-S4: a user-friendly system for flexible, customizable, and large-scale social simulation
Xuhui Zhou | Zhe Su | Sophie Feng | Jiaxu Zhou | Jen-tse Huang | Hsien-Te Kao | Spencer Lynch | Svitlana Volkova | Tongshuang Wu | Anita Woolley | Hao Zhu | Maarten Sap
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (System Demonstrations)

Social simulation through large language model (LLM) agents is a promising approach to explore and validate social science hypotheses.We present SOTOPIA-S4, a fast, flexible, and scalable social simulation system that addresses the technical barriers of current frameworks while enabling practitioners to generate realistic, multi-turn and multi-party interactions with customizable evaluation metrics for hypothesis testing. SOTOPIA-S4 comes as a pip package that contains a simulation engine, an API server with flexible RESTful APIs for simulation management, and a web interface that enables both technical and non-technical users to design, run, and analyze simulations without programming. We demonstrate the usefulness of SOTOPIA-S4 with two use cases involving dyadic hiring negotiation scenarios and multi-party planning scenarios.