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Project
Automatic detection of (potential) factors in the source text leading to gender bias in machine translation
Information
Project Team
Organisations
Outputs and Outcomes
Publications
Mind the inclusivity gap : multilingual gender-neutral translation evaluation with mGeNTE
Beatrice Savoldi
Giuseppe Attanasio
Eleonora Cupin
Eleni Gkovedarou
Janica Hackenbuchner
Anne Lauscher
Matteo Negri
Andrea Piergentili
Manjinder Thind
Luisa Bentivogli
C3
Conference
2025
Glitter : a multi-sentence, multi-reference benchmark for gender-fair German machine translation
A. Pranav
Janica Hackenbuchner
Giuseppe Attanasio
Manuel Lardelli
Anne Lauscher
C3
Conference
2025
GENDEROUS : machine translation and cross-linguistic evaluation of a gender-ambiguous dataset
Janica Hackenbuchner
Eleni Gkovedarou
Joke Daems
C3
Conference
2025
Gender bias and the role of context in human perception and machine translation
Janica Hackenbuchner
Joke Daems
Arda Tezcan
C3
Conference
2025
Can we interpret gender? Using contrastive explanations to understand gender choices by translation systems
Janica Hackenbuchner
Joke Daems
Arda Tezcan
C3
Conference
2025
Mind the inclusivity gap : multilingual gender-neutral translation evaluation with mGeNTE
Beatrice Savoldi
Giuseppe Attanasio
Eleonora Cupin
Eleni Gkovedarou
Janica Hackenbuchner
Anne Lauscher
Matteo Negri
Andrea Piergentili
Manjinder Thind
Luisa Bentivogli
C1
Conference
2025
Glitter : a multi-sentence, multi-reference benchmark for gender-fair German machine translation
A. Pranav
Janica Hackenbuchner
Giuseppe Attanasio
Manuel Lardelli
Anne Lauscher
C1
Conference
2025
GENDEROUS : machine translation and cross-linguistic evaluation of a gender-ambiguous dataset
Janica Hackenbuchner
Eleni Gkovedarou
Joke Daems
C1
Conference
2025
Gender bias and the role of context in human perception and machine translation
Janica Hackenbuchner
Joke Daems
Arda Tezcan
A2
Journal Article
in
COMPUTATIONAL LINGUISTICS IN THE NETHERLANDS JOURNAL
2025
Automatic detection of (potential) factors in the source text leading to gender bias in machine translation
Janica Hackenbuchner
Joke Daems
Arda Tezcan
C3
Conference
2024
You shall know a word’s gender by the company it keeps : comparing the role of context in human gender assumptions with MT
Janica Hackenbuchner
Aaron Maladry
Joke Daems
Arda Tezcan
C3
Conference
2024
Systematic, stereotypical or an educated guess? Gender inference by humans and machine translation systems of words in and out of context
Janica Hackenbuchner
Joke Daems
Arda Tezcan
C3
Conference
2024
Automatic detection of (potential) factors in the source text leading to gender bias in machine translation
Janica Hackenbuchner
Arda Tezcan
Joke Daems
C3
Conference
2024
You shall know a word’s gender by the company it keeps : comparing the role of context in human gender assumptions with MT
Janica Hackenbuchner
Arda Tezcan
Aaron Maladry
Joke Daems
C1
Conference
2024