Key References
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Ahnert, G., Haensch, A. C., Plank, B., & Strohmaier, M. (2025). Survey Response Generation: Generating Closed-Ended Survey Responses In-Silico with Large Language Models. arXiv preprint arXiv:2510.11586.
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Argyle, L. P., Busby, E. C., Fulda, N., Gubler, J. R., Rytting, C., & Wingate, D. (2023). Out of one, many: Using language models to simulate human samples. Political Analysis, 31(3), 337-351.
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Kreutner, M., Rupprecht, J., Ahnert, G., Salem, A., & Strohmaier, M. (2025). QSTN: A Modular Framework for Robust Questionnaire Inference with Large Language Models. arXiv preprint arXiv:2512.08646.
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Lutz, M., Sen, I., Ahnert, G., Rogers, E., & Strohmaier, M. (2025). The Prompt Makes the Person(a): A Systematic Evaluation of Sociodemographic Persona Prompting for Large Language Models. Findings of the Association for Computational Linguistics: EMNLP 2025 (pp. 23212–23237).
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Rothschild, D. M., Buskirk, T. D., Eckman, S., Hillygus, D. S., Kreuter, F., & Lazer, D. (2025). Successfully Navigating the Disruption AI will Bring to Survey Research.
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Sen, I., Lutz, M., Rogers, E., Garcia, D., & Strohmaier, M. (2025). Missing the Margins: A Systematic Literature Review on the Demographic Representativeness of LLMs. Findings of the Association for Computational Linguistics: ACL 2025 (pp. 24263–24289).