27 citations · 35 across the 2 of their papers we have counts for
3 papers
Impact of Gender Debiased Word Embeddings in Language Modeling
Christine Basta, Marta R. Costa-jussà
Gender, race and social biases have recently been detected as evident examples of unfairness in applications of Natural Language Processing. A key path towards fairness is to under…
Gender Bias in Multilingual Neural Machine Translation: The Architecture Matters
Marta R. Costa-jussà, Carlos Escolano, Christine Basta +3
Multilingual Neural Machine Translation architectures mainly differ in the amount of sharing modules and parameters among languages. In this paper, and from an algorithmic perspect…
Evaluating the Underlying Gender Bias in Contextualized Word Embeddings
Christine Basta, Marta R. Costa-jussà, Noe Casas
Gender bias is highly impacting natural language processing applications. Word embeddings have clearly been proven both to keep and amplify gender biases that are present in curren…