activity
20242026
collaborators

5 papers

cs.CL2026

Do Psychometric Tests Work for Large Language Models? Evaluation of Tests on Sexism, Racism, and Morality

Jana Jung, Marlene Lutz, Indira Sen +1

Psychometric tests are increasingly used to assess psychological constructs in large language models (LLMs). However, it remains unclear whether these tests -- originally developed…

cs.CY2025

Missing the Margins: A Systematic Literature Review on the Demographic Representativeness of LLMs

Indira Sen, Marlene Lutz, Elisa Rogers +2

Many applications of Large Language Models (LLMs) require them to either simulate people or offer personalized functionality, making the demographic representativeness of LLMs cruc…

cs.CL2025

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…

cs.CY2025

Only a Little to the Left: A Theory-grounded Measure of Political Bias in Large Language Models

Mats Faulborn, Indira Sen, Max Pellert +2

Prompt-based language models like GPT4 and LLaMa have been used for a wide variety of use cases such as simulating agents, searching for information, or for content analysis. For a…

cs.CY2024

Robustness and Confounders in the Demographic Alignment of LLMs with Human Perceptions of Offensiveness

Shayan Alipour, Indira Sen, Mattia Samory +1

Large language models (LLMs) are known to exhibit demographic biases, yet few studies systematically evaluate these biases across multiple datasets or account for confounding facto…