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From ChatGPT to DeepSeek: Can LLMs Simulate Humanity?
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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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Cited by 1 Pith paper
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Whispers of Many Shores: Cultural Alignment through Collaborative Cultural Expertise
A multi-agent router that selects culturally specialized LLM personas reports a jump in self-scored cultural alignment from 0.208 to 0.820, but the metric and the claimed method are not independently validated.
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