MT-GenEval: A Counterfactual and Contextual Dataset for Evaluating Gender Accuracy in Machine Translation

2 November 2022

Papers citing "MT-GenEval: A Counterfactual and Contextual Dataset for Evaluating Gender Accuracy in Machine Translation"

7 / 7 papers shown

Title
FairTranslate: An English-French Dataset for Gender Bias Evaluation in Machine Translation by Overcoming Gender Binarity Fanny Jourdan Yannick Chevalier Cécile Favre 27 0 0 22 Apr 2025
Assumed Identities: Quantifying Gender Bias in Machine Translation of Gender-Ambiguous Occupational Terms Orfeas Menis Mastromichalakis Giorgos Filandrianos Maria Symeonaki Giorgos Stamou 62 0 0 06 Mar 2025
GATE X-E : A Challenge Set for Gender-Fair Translations from Weakly-Gendered Languages Spencer Rarrick Ranjita Naik Sundar Poudel Vishal Chowdhary 36 1 0 22 Feb 2024
Promoting Target Data in Context-aware Neural Machine Translation Harritxu Gete Thierry Etchegoyhen 29 1 0 09 Feb 2024
Target-Agnostic Gender-Aware Contrastive Learning for Mitigating Bias in Multilingual Machine Translation Minwoo Lee Hyukhun Koh Kang-il Lee Dongdong Zhang Minsu Kim Kyomin Jung 32 9 0 23 May 2023
GENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena Eva Vanmassenhove J. Monti 31 14 0 05 Aug 2021
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,746 0 26 Sep 2016