Papers by Georg Ahnert

3 papers
Survey Response Generation: Generating Closed-Ended Survey Responses In-Silico with Large Language Models (2026.acl-long)

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Challenge: Existing studies focus on generating closed-ended survey responses with large language models, whereas LLMs are typically trained to generate open-ended text.
Approach: They evaluate the impact of various Survey Response Generation Methods on simulated responses by generating closed-ended responses from large language models.
Outcome: The proposed methods perform best in individual-level and subpopulation-level alignment.
The Prompt Makes the Person(a): A Systematic Evaluation of Sociodemographic Persona Prompting for Large Language Models (2025.findings-emnlp)

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Challenge: persona prompting is increasingly used in large language models to simulate views of various sociodemographic groups.
Approach: They use open-source LLMs to study how persona prompts influence LLM simulations . they use role adoption formats and demographic priming strategies to study marginalized groups .
Outcome: The results show that the choice of demographic priming and role adoption strategy significantly impacts their portrayal.
QSTN: A Modular Framework for Robust Questionnaire Inference with Large Language Models (2026.eacl-demo)

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Challenge: Questionnaire-like prompts have become an important format to probe, assess, and utilize large language models (LLMs)
Approach: They propose an open-source Python framework for generating responses from questionnaire-style prompts to support in-silico surveys and annotation tasks with large language models (LLMs).
Outcome: The proposed framework can be used to generate responses from questionnaire-style prompts and to perform annotations on large language models.

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