@inproceedings{wisniewski-etal-2021-screening,
title = "Screening Gender Transfer in Neural Machine Translation",
author = "Wisniewski, Guillaume and
Zhu, Lichao and
Bailler, Nicolas and
Yvon, Fran{\c{c}}ois",
editor = "Bastings, Jasmijn and
Belinkov, Yonatan and
Dupoux, Emmanuel and
Giulianelli, Mario and
Hupkes, Dieuwke and
Pinter, Yuval and
Sajjad, Hassan",
booktitle = "Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP",
month = nov,
year = "2021",
address = "Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.blackboxnlp-1.24/",
doi = "10.18653/v1/2021.blackboxnlp-1.24",
pages = "311--321",
abstract = "This paper aims at identifying the information flow in state-of-the-art machine translation systems, taking as example the transfer of gender when translating from French into English. Using a controlled set of examples, we experiment several ways to investigate how gender information circulates in a encoder-decoder architecture considering both probing techniques as well as interventions on the internal representations used in the MT system. Our results show that gender information can be found in all token representations built by the encoder and the decoder and lead us to conclude that there are multiple pathways for gender transfer."
}
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%0 Conference Proceedings
%T Screening Gender Transfer in Neural Machine Translation
%A Wisniewski, Guillaume
%A Zhu, Lichao
%A Bailler, Nicolas
%A Yvon, François
%Y Bastings, Jasmijn
%Y Belinkov, Yonatan
%Y Dupoux, Emmanuel
%Y Giulianelli, Mario
%Y Hupkes, Dieuwke
%Y Pinter, Yuval
%Y Sajjad, Hassan
%S Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F wisniewski-etal-2021-screening
%X This paper aims at identifying the information flow in state-of-the-art machine translation systems, taking as example the transfer of gender when translating from French into English. Using a controlled set of examples, we experiment several ways to investigate how gender information circulates in a encoder-decoder architecture considering both probing techniques as well as interventions on the internal representations used in the MT system. Our results show that gender information can be found in all token representations built by the encoder and the decoder and lead us to conclude that there are multiple pathways for gender transfer.
%R 10.18653/v1/2021.blackboxnlp-1.24
%U https://aclanthology.org/2021.blackboxnlp-1.24/
%U https://doi.org/10.18653/v1/2021.blackboxnlp-1.24
%P 311-321
Markdown (Informal)
[Screening Gender Transfer in Neural Machine Translation](https://aclanthology.org/2021.blackboxnlp-1.24/) (Wisniewski et al., BlackboxNLP 2021)
ACL
- Guillaume Wisniewski, Lichao Zhu, Nicolas Bailler, and François Yvon. 2021. Screening Gender Transfer in Neural Machine Translation. In Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, pages 311–321, Punta Cana, Dominican Republic. Association for Computational Linguistics.