1 citations · 1 across the 2 of their papers we have counts for
4 papers
How far can bias go? Tracing bias from pretraining data to alignment
Marion Thaler, Abdullatif Köksal, Alina Leidinger +2
As LLMs are increasingly integrated into user-facing applications, addressing biases that perpetuate societal inequalities is crucial. While much work has gone into measuring or mi…
How Are LLMs Mitigating Stereotyping Harms? Learning from Search Engine Studies
Alina Leidinger, Richard Rogers
With the widespread availability of LLMs since the release of ChatGPT and increased public scrutiny, commercial model development appears to have focused their efforts on 'safety'…
Are LLMs classical or nonmonotonic reasoners? Lessons from generics
Alina Leidinger, Robert van Rooij, Ekaterina Shutova
Recent scholarship on reasoning in LLMs has supplied evidence of impressive performance and flexible adaptation to machine generated or human feedback. Nonmonotonic reasoning, cruc…
CIVICS: Building a Dataset for Examining Culturally-Informed Values in Large Language Models
Giada Pistilli, Alina Leidinger, Yacine Jernite +3
This paper introduces the "CIVICS: Culturally-Informed & Values-Inclusive Corpus for Societal impacts" dataset, designed to evaluate the social and cultural variation of Large Lang…