3 papers
cs.CL2025
Large Means Left: Political Bias in Large Language Models Increases with Their Number of Parameters
David Exler, Mark Schutera, Markus Reischl +1
With the increasing prevalence of artificial intelligence, careful evaluation of inherent biases needs to be conducted to form the basis for alleviating the effects these predispos…
cs.CL2024
PERSONA: A Reproducible Testbed for Pluralistic Alignment
Louis Castricato, Nathan Lile, Rafael Rafailov +2
The rapid advancement of language models (LMs) necessitates robust alignment with diverse user values. However, current preference optimization approaches often fail to capture the…
cs.CL2024
Assessing Political Bias in Large Language Models
Luca Rettenberger, Markus Reischl, Mark Schutera
The assessment of bias within Large Language Models (LLMs) has emerged as a critical concern in the contemporary discourse surrounding Artificial Intelligence (AI) in the context o…