4 papers
One Persona, Many Cues, Different Results: How Sociodemographic Cues Impact LLM Personalization
Franziska Weeber, Vera Neplenbroek, Jan Batzner +1
Personalization of LLMs by sociodemographic subgroup often improves user experience, but can also introduce or amplify biases and unfair outcomes across groups. Prior work has empl…
Beyond Marginal Distributions: A Framework to Evaluate the Representativeness of Demographic-Aligned LLMs
Tristan Williams, Franziska Weeber, Sebastian Padó +1
Large language models are increasingly used to represent human opinions, values, or beliefs, and their steerability towards these ideals is an active area of research. Existing wor…
PRSM: A Measure to Evaluate CLIP's Robustness Against Paraphrases
Udo Schlegel, Franziska Weeber, Jian Lan +1
Contrastive Language-Image Pre-training (CLIP) is a widely used multimodal model that aligns text and image representations through large-scale training. While it performs strongly…
Do Political Opinions Transfer Between Western Languages? An Analysis of Unaligned and Aligned Multilingual LLMs
Franziska Weeber, Tanise Ceron, Sebastian Padó
Public opinion surveys show cross-cultural differences in political opinions between socio-cultural contexts. However, there is no clear evidence whether these differences translat…