From ChatGPT to DeepSeek: Can LLMs Simulate Humanity?

Fuente: arXiv
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Autori principali: Wang, Qian, Tang, Zhenheng, He, Bingsheng
Natura: Preprint
Pubblicazione: 2025
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author Wang, Qian
Tang, Zhenheng
He, Bingsheng
author_facet Wang, Qian
Tang, Zhenheng
He, Bingsheng
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2502_18210
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle From ChatGPT to DeepSeek: Can LLMs Simulate Humanity?
Wang, Qian
Tang, Zhenheng
He, Bingsheng
Computers and Society
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.
title From ChatGPT to DeepSeek: Can LLMs Simulate Humanity?
topic Computers and Society
url https://arxiv.org/abs/2502.18210