From ChatGPT to DeepSeek: Can LLMs Simulate Humanity?

• URL: http://arxiv.org/abs/2502.18210v1
• Date: Tue, 25 Feb 2025 13:54:47 GMT
• Title: From ChatGPT to DeepSeek: Can LLMs Simulate Humanity?
• Authors: Qian Wang, Zhenheng Tang, Bingsheng He,
• Abstract summary: Large Language Models (LLMs) have become a promising method for exploring complex human social behaviors.<n>Recent studies highlight discrepancies between simulated and real-world interactions.
• Score: 32.93460040317926
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Simulation powered by Large Language Models (LLMs) has become a promising method for exploring complex human social behaviors. However, the application of LLMs in simulations presents significant challenges, particularly regarding their capacity to accurately replicate the complexities of human behaviors and societal dynamics, as evidenced by recent studies highlighting discrepancies between simulated and real-world interactions. We rethink LLM-based simulations by emphasizing both their limitations and the necessities for advancing LLM simulations. By critically examining these challenges, we aim to offer actionable insights and strategies for enhancing the applicability of LLM simulations in human society in the future.

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