Gender issues in machine translation

By Johanna Monti. 2020

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Matteo Negri
2. Marco Turchi
3. Beatrice Savoldi
4. Marco Gaido
5. Luisa Bentivogli
6. Changhan Wang
7. Juan Pino
8. Yun Tang

Citations in the corpus

• Gender Bias in Machine Translation (2021, methodology): “We go beyond surveys restricted to monolingual NLP (Sun et al., 2019) or that are more limited in scope (Costa-jussà, 2019; Monti, 2020), and present the first comprehensive review of gender bias in MT.”