LLMs simulate survey respondents, offering new social science research tools

Researchers have developed a new benchmark called LLM-S^3 to evaluate how well large language models can simulate human respondents in surveys. The benchmark includes 11 real-world datasets across various sociological domains. Experiments using GPT-3.5/4 Turbo and LLaMA 3.0/3.1-8B showed consistent performance trends and highlighted how prompt design impacts simulation accuracy. AI

影响 Introduces a new benchmark for evaluating LLM simulation capabilities, potentially improving data collection methods in social sciences.

排序理由 The cluster contains an academic paper introducing a new benchmark for evaluating LLMs in survey simulation.

在 arXiv cs.AI 阅读 →

• arXiv
• GPT-3.5
• GPT-4 Turbo
• LLaMA 3.0
• LLaMA 3.1-8B
• LLM-S^3

• 论文
• 其他

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