5 papers
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…
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…
Colombian Waitresses y Jueces canadienses: Gender and Country Biases in Occupation Recommendations from LLMs
Elisa Forcada Rodríguez, 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…
BasqueParl: A Bilingual Corpus of Basque Parliamentary Transcriptions
Nayla Escribano, Jon Ander González, Julen Orbegozo-Terradillos +4
Parliamentary transcripts provide a valuable resource to understand the reality and know about the most important facts that occur over time in our societies. Furthermore, the poli…
Does Corpus Quality Really Matter for Low-Resource Languages?
Mikel Artetxe, Itziar Aldabe, Rodrigo Agerri +2
The vast majority of non-English corpora are derived from automatically filtered versions of CommonCrawl. While prior work has identified major issues on the quality of these datas…