3 citations · 3 across the 10 of their papers we have counts for
10 papers
Total Simulated Survey Error: Designing and Diagnosing Survey Responses from Large Language Models
Indira Sen, Georg Ahnert, Leah von der Heyde +3
Large Language models (LLMs), having been trained on vast amounts of human-generated data, may encode the attitudes and behaviors of these humans. As such, LLMs show promise in mim…
In-Context Learning for the Imputation of Public Opinion Data with Large Language Models
Tobias Holtdirk, Georg Ahnert, Joseph W Sakshaug +1
Large language models have been widely evaluated as simulators of individual survey responses. In practice, however, fully unobserved responses are rare; the dominant problem is pa…
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…
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…
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…
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…
Simulating Persuasive Dialogues on Meat Reduction with Generative Agents
Georg Ahnert, Elena Wurth, Markus Strohmaier +1
Meat reduction benefits human and planetary health, but social norms keep meat central in shared meals. To date, the development of communication strategies that promote meat reduc…
Extracting Affect Aggregates from Longitudinal Social Media Data with Temporal Adapters for Large Language Models
Georg Ahnert, Max Pellert, David Garcia +1
This paper proposes temporally aligned Large Language Models (LLMs) as a tool for longitudinal analysis of social media data. We fine-tune Temporal Adapters for Llama 3 8B on full…
Fair Pairs: Fairness-Aware Ranking Recovery from Pairwise Comparisons
Georg Ahnert, Antonio Ferrara, Claudia Wagner
Pairwise comparisons based on human judgements are an effective method for determining rankings of items or individuals. However, as human biases perpetuate from pairwise compariso…
The FairCeptron: A Framework for Measuring Human Perceptions of Algorithmic Fairness
Georg Ahnert, Ivan Smirnov, Florian Lemmerich +2
Measures of algorithmic fairness often do not account for human perceptions of fairness that can substantially vary between different sociodemographics and stakeholders. The FairCe…