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Large Language Models (LLMs) excel in text generation and understanding, especially in simulating socio-political and economic patterns, serving as an alternative to traditional surveys.
Language models are few-shot learners
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Language models (mostly) know what they know
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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. In Advances in Neural Information Processing Systems , S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, and A. Oh (Eds.), Vol. 35. Curran Associates, Inc., 24824–24837
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Can large language models help predict results from a complex behavioural science study?
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BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages
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Can AI language models replace human participants?
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Biases in large language models: origins, inventory, and discussion
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Whose opinions do language models reflect?. In International Conference on Machine Learning . PMLR, 29971–30004
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Predicting results of social science experiments using large language models
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Large language models cannot replace human participants because they cannot portray identity groups
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PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts
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Can large language models transform computational social science?
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