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SOTOPIA-S4: a user-friendly system for flexible, customizable, and large-scale social simulation
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Social simulation through large language model (LLM) agents is a promising approach to explore and validate hypotheses related to social science questions and LLM agents behavior. 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 multi-turn and multi-party LLM-based 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 and multi-party planning scenarios.
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Cited by 1 Pith paper
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YuLan-OneSim: Towards the Next Generation of Social Simulator with Large Language Models
YuLan-OneSim combines natural-language scenario generation, 50 prebuilt simulation scenarios, feedback-driven agent fine-tuning, 100,000-agent scale, and an automated AI social researcher into one social simulation platform.
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