Anna Currey, Maria Nadejde, Raghavendra Reddy Pappagari, Mia Mayer, Stanislas Lauly, Xing Niu, Benjamin Hsu, Georgiana Dinu. MT-GenEval: A Counterfactual and Contextual Dataset for Evaluating Gender Accuracy in Machine Translation. In Yoav Goldberg, Zornitsa Kozareva, Yue Zhang, editors, Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7-11. pages 4287-4299, Association for Computational Linguistics, 2022. [doi]
@inproceedings{CurreyNPMLNHD22,
title = {MT-GenEval: A Counterfactual and Contextual Dataset for Evaluating Gender Accuracy in Machine Translation},
author = {Anna Currey and Maria Nadejde and Raghavendra Reddy Pappagari and Mia Mayer and Stanislas Lauly and Xing Niu and Benjamin Hsu and Georgiana Dinu},
year = {2022},
url = {https://aclanthology.org/2022.emnlp-main.288},
researchr = {https://researchr.org/publication/CurreyNPMLNHD22},
cites = {0},
citedby = {0},
pages = {4287-4299},
booktitle = {Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7-11},
editor = {Yoav Goldberg and Zornitsa Kozareva and Yue Zhang},
publisher = {Association for Computational Linguistics},
}