| Přispěvatelé: |
Macken, Lieve, Rufener, Andrew, Van den Bogaert, Joachim, Daems, Joke, Tezcan, Arda, Vanroy, Bram, Fonteyne, Margot, Barrault, Loïc, Costa-jussà, Marta R., Kemp, Ellie, Pilos, Spyridon, Declercq, Christophe, Koponen, Maarit, Forcada, Mikel L., Scarton, Carolina, Moniz, Helena |
| Popis: |
This paper presents the project initiated by the BiasByUs team resulting from the 2021 Artificially Correct Hackaton. We briefly explain our winning participation in the hackaton, tackling the challenge on ‘Database and detection of gender bi-as in A.I. translations’, we highlight the importance of gender bias in Machine Translation (MT), and describe our pro-posed solution to the challenge, the cur-rent status of the project, and our envi-sioned future collaborations and re-search. |
