5 papers · 1 filter
Survey Response Generation: Generating Closed-Ended Survey Responses In-Silico with Large Language Models
Georg Ahnert, Anna-Carolina Haensch, Barbara Plank +1
Many in-silico simulations of human survey responses with large language models (LLMs) focus on generating closed-ended survey responses, whereas LLMs are typically trained to gene…
German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies
Jens Rupprecht, Leon Fröhling, Claudia Wagner +1
The use of Large Language Models (LLMs) for simulating human perspectives via persona prompting is gaining traction in computational social science. However, well-curated, empirica…
QSTN: A Modular Framework for Robust Questionnaire Inference with Large Language Models
Maximilian Kreutner, Jens Rupprecht, Georg Ahnert +2
We introduce QSTN, an open-source Python framework for systematically generating responses from questionnaire-style prompts to support in-silico surveys and annotation tasks with l…
Prompt Perturbations Reveal Human-Like Biases in Large Language Model Survey Responses
Jens Rupprecht, Georg Ahnert, Markus Strohmaier
Large Language Models (LLMs) are increasingly used as proxies for human subjects in social science surveys, but their reliability and susceptibility to known human-like response bi…
The Prompt Makes the Person(a): A Systematic Evaluation of Sociodemographic Persona Prompting for Large Language Models
Marlene Lutz, Indira Sen, Georg Ahnert +2
Persona prompting is increasingly used in large language models (LLMs) to simulate views of various sociodemographic groups. However, how a persona prompt is formulated can signifi…