{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/gensim-a-general-social-simulation-platform","title":"GenSim: A General Social Simulation Platform with Large Language Model based Agents","arxiv_id":"2410.04360","date":"2024-10-06","proceeding":null,"authors":["Jiakai Tang","Heyang Gao","Xuchen Pan","Lei Wang","Haoran Tan","Dawei Gao","Yushuo Chen","Xu Chen","Yankai Lin","Yaliang Li","Bolin Ding","Jingren Zhou","Jun Wang","Ji-Rong Wen"],"abstract":"With the rapid advancement of large language models (LLMs), recent years have witnessed many promising studies on leveraging LLM-based agents to simulate human social behavior. While prior work has demonstrated significant potential across various domains, much of it has focused on specific scenarios involving a limited number of agents and has lacked the ability to adapt when errors occur during simulation. To overcome these limitations, we propose a novel LLM-agent-based simulation platform called \\textit{GenSim}, which: (1) \\textbf{Abstracts a set of general functions} to simplify the simulation of customized social scenarios; (2) \\textbf{Supports one hundred thousand agents} to better simulate large-scale populations in real-world contexts; (3) \\textbf{Incorporates error-correction mechanisms} to ensure more reliable and long-term simulations. To evaluate our platform, we assess both the efficiency of large-scale agent simulations and the effectiveness of the error-correction mechanisms. To our knowledge, GenSim represents an initial step toward a general, large-scale, and correctable social simulation platform based on LLM agents, promising to further advance the field of social science.","url_abs":"https://arxiv.org/abs/2410.04360v2","url_pdf":"https://arxiv.org/pdf/2410.04360v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"gensim-a-general-social-simulation-platform","repo_url":"https://github.com/TangJiakai/GenSim","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"large-language-model","task_name":"Large Language Model"}],"methods":[{"method_slug":"set","method_name":"SET"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2410.04360","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.04360"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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