Jiaxu Zhou
2025
SOTOPIA-S4: a user-friendly system for flexible, customizable, and large-scale social simulation
Xuhui Zhou
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Zhe Su
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Sophie Feng
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Jiaxu Zhou
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Jen-tse Huang
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Hsien-Te Kao
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Spencer Lynch
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Svitlana Volkova
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Tongshuang Wu
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Anita Woolley
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Hao Zhu
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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.
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Co-authors
- Sophie Feng 1
- Jen-tse Huang 1
- Hsien-Te Kao 1
- Spencer Lynch 1
- Maarten Sap 1
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