@inproceedings{ruiter-etal-2019-self,
title = "Self-Supervised Neural Machine Translation",
author = "Ruiter, Dana and
Espa{\~n}a-Bonet, Cristina and
van Genabith, Josef",
editor = "Korhonen, Anna and
Traum, David and
M{\`a}rquez, Llu{\'i}s",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://preview.aclanthology.org/fix-sig-urls/P19-1178/",
doi = "10.18653/v1/P19-1178",
pages = "1828--1834",
abstract = "We present a simple new method where an emergent NMT system is used for simultaneously selecting training data and learning internal NMT representations. This is done in a self-supervised way without parallel data, in such a way that both tasks enhance each other during training. The method is language independent, introduces no additional hyper-parameters, and achieves BLEU scores of 29.21 (en2fr) and 27.36 (fr2en) on newstest2014 using English and French Wikipedia data for training."
}
Markdown (Informal)
[Self-Supervised Neural Machine Translation](https://preview.aclanthology.org/fix-sig-urls/P19-1178/) (Ruiter et al., ACL 2019)
ACL
- Dana Ruiter, Cristina España-Bonet, and Josef van Genabith. 2019. Self-Supervised Neural Machine Translation. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 1828–1834, Florence, Italy. Association for Computational Linguistics.