3 papers
cs.CL2026
Gender Bias in MT for a Genderless Language: New Benchmarks for Basque
Amaia Murillo, Olatz-Perez-de-Viñaspre, Naiara Perez
Large language models (LLMs) and machine translation (MT) systems are increasingly used in our daily lives, but their outputs can reproduce gender bias present in the training data…
cs.CL2025
Colombian Waitresses y Jueces canadienses: Gender and Country Biases in Occupation Recommendations from LLMs
Elisa Forcada RodrÃguez, Olatz Perez-de-Viñaspre, Jon Ander Campos +2
One of the goals of fairness research in NLP is to measure and mitigate stereotypical biases that are propagated by NLP systems. However, such work tends to focus on single axes of…
cs.CL2025
EsBBQ and CaBBQ: The Spanish and Catalan Bias Benchmarks for Question Answering
Valle Ruiz-Fernández, Mario Mina, Júlia Falcão +4
Previous literature has largely shown that Large Language Models (LLMs) perpetuate social biases learnt from their pre-training data. Given the notable lack of resources for social…