Findings of the First Shared Task on Lifelong Learning Machine Translation
Loïc Barrault, Magdalena Biesialska, Marta R. Costa-jussà, Fethi Bougares, Olivier Galibert
Abstract
A lifelong learning system can adapt to new data without forgetting previously acquired knowledge. In this paper, we introduce the first benchmark for lifelong learning machine translation. For this purpose, we provide training, lifelong and test data sets for two language pairs: English-German and English-French. Additionally, we report the results of our baseline systems, which we make available to the public. The goal of this shared task is to encourage research on the emerging topic of lifelong learning machine translation.- Anthology ID:
- 2020.wmt-1.2
- Volume:
- Proceedings of the Fifth Conference on Machine Translation
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Yvette Graham, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 56–64
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.2
- DOI:
- Bibkey:
- Cite (ACL):
- Loïc Barrault, Magdalena Biesialska, Marta R. Costa-jussà, Fethi Bougares, and Olivier Galibert. 2020. Findings of the First Shared Task on Lifelong Learning Machine Translation. In Proceedings of the Fifth Conference on Machine Translation, pages 56–64, Online. Association for Computational Linguistics.
- Cite (Informal):
- Findings of the First Shared Task on Lifelong Learning Machine Translation (Barrault et al., WMT 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.wmt-1.2.pdf
- Video:
- https://slideslive.com/38939679
Export citation
@inproceedings{barrault-etal-2020-findings-first,
title = "Findings of the First Shared Task on Lifelong Learning Machine Translation",
author = {Barrault, Lo{\"\i}c and
Biesialska, Magdalena and
Costa-juss{\`a}, Marta R. and
Bougares, Fethi and
Galibert, Olivier},
editor = {Barrault, Lo{\"\i}c and
Bojar, Ond{\v{r}}ej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-juss{\`a}, Marta R. and
Federmann, Christian and
Fishel, Mark and
Fraser, Alexander and
Graham, Yvette and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Morishita, Makoto and
Monz, Christof and
Nagata, Masaaki and
Nakazawa, Toshiaki and
Negri, Matteo},
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wmt-1.2",
pages = "56--64",
abstract = "A lifelong learning system can adapt to new data without forgetting previously acquired knowledge. In this paper, we introduce the first benchmark for lifelong learning machine translation. For this purpose, we provide training, lifelong and test data sets for two language pairs: English-German and English-French. Additionally, we report the results of our baseline systems, which we make available to the public. The goal of this shared task is to encourage research on the emerging topic of lifelong learning machine translation.",
}
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%0 Conference Proceedings %T Findings of the First Shared Task on Lifelong Learning Machine Translation %A Barrault, Loïc %A Biesialska, Magdalena %A Costa-jussà, Marta R. %A Bougares, Fethi %A Galibert, Olivier %Y Barrault, Loïc %Y Bojar, Ondřej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussà, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Graham, Yvette %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Martins, André %Y Morishita, Makoto %Y Monz, Christof %Y Nagata, Masaaki %Y Nakazawa, Toshiaki %Y Negri, Matteo %S Proceedings of the Fifth Conference on Machine Translation %D 2020 %8 November %I Association for Computational Linguistics %C Online %F barrault-etal-2020-findings-first %X A lifelong learning system can adapt to new data without forgetting previously acquired knowledge. In this paper, we introduce the first benchmark for lifelong learning machine translation. For this purpose, we provide training, lifelong and test data sets for two language pairs: English-German and English-French. Additionally, we report the results of our baseline systems, which we make available to the public. The goal of this shared task is to encourage research on the emerging topic of lifelong learning machine translation. %U https://aclanthology.org/2020.wmt-1.2 %P 56-64
Markdown (Informal)
[Findings of the First Shared Task on Lifelong Learning Machine Translation](https://aclanthology.org/2020.wmt-1.2) (Barrault et al., WMT 2020)
- Findings of the First Shared Task on Lifelong Learning Machine Translation (Barrault et al., WMT 2020)
ACL
- Loïc Barrault, Magdalena Biesialska, Marta R. Costa-jussà, Fethi Bougares, and Olivier Galibert. 2020. Findings of the First Shared Task on Lifelong Learning Machine Translation. In Proceedings of the Fifth Conference on Machine Translation, pages 56–64, Online. Association for Computational Linguistics.