10 papers
Effects of Answer Format Variation on Gender Bias in Large Language Models
Ksenia Merzlyakova, Sebastian Padó, Franziska Weeber
Gender bias or other social biases in large language models (LLMs) are frequently evaluated with question answering or survey benchmarks where the LLM needs to give a response in a…
Gaze Behavior in Visual World Experiments Can be Modeled With Off-the-shelf Language-Vision Encoders
Rahul Murali Shankar, Titus von der Malsburg, Sebastian Padó
The recent advances in neural language models have also spurred much work in computational psycholinguistics, asking whether neural LMs are also promising models of human language…
Understanding the Impact of Linguistic Realization Choices on LLM Stance with Causal Tracing
Langchen Huang, Sebastian Padó, Franziska Weeber
Large language models (LLMs) are known to be sensitive to prompt and input formulations. However, existing studies have focused on lexical realization and largely ignored construct…
Finding Sense in Nonsense with Generated Contexts: Perspectives from Humans and Language Models
Katrina Olsen, Sebastian Padó
Nonsensical and anomalous sentences have been instrumental in the development of computational models of semantic interpretation. A core challenge is to distinguish between what is…
Democratizing News Recommenders: Modeling Multiple Perspectives for News Candidate Generation with VQ-VAE
Hardy, Sebastian Padó, Amelie Wührl +1
News Recommender Systems (NRS) shape what users read, whose perspectives they encounter, and influence public discourse. Yet their design is value-laden: intentionally or not, NRS…
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…