Correct Metadata for
Abstract
This project aims to study the impact of adapting neural machine translation (NMT) systems through translation exemplars, determine the optimal similarity metric(s) for retrieving informative exemplars, and, verify the usefulness of this approach for domain adaptation of NMT systems.- Anthology ID:
- 2022.eamt-1.31
- Volume:
- Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
- Month:
- June
- Year:
- 2022
- Address:
- Ghent, Belgium
- Editors:
- Helena Moniz, Lieve Macken, Andrew Rufener, Loïc Barrault, Marta R. Costa-jussà, Christophe Declercq, Maarit Koponen, Ellie Kemp, Spyridon Pilos, Mikel L. Forcada, Carolina Scarton, Joachim Van den Bogaert, Joke Daems, Arda Tezcan, Bram Vanroy, Margot Fonteyne
- Venue:
- EAMT
- SIG:
- Publisher:
- European Association for Machine Translation
- Note:
- Pages:
- 283–284
- Language:
- URL:
- https://aclanthology.org/2022.eamt-1.31/
- DOI:
- Bibkey:
- Cite (ACL):
- Arda Tezcan. 2022. Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 283–284, Ghent, Belgium. European Association for Machine Translation.
- Cite (Informal):
- Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars (Tezcan, EAMT 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.eamt-1.31.pdf
Export citation
@inproceedings{tezcan-2022-dynamic,
title = "Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars",
author = "Tezcan, Arda",
editor = {Moniz, Helena and
Macken, Lieve and
Rufener, Andrew and
Barrault, Lo{\"i}c and
Costa-juss{\`a}, Marta R. and
Declercq, Christophe and
Koponen, Maarit and
Kemp, Ellie and
Pilos, Spyridon and
Forcada, Mikel L. and
Scarton, Carolina and
Van den Bogaert, Joachim and
Daems, Joke and
Tezcan, Arda and
Vanroy, Bram and
Fonteyne, Margot},
booktitle = "Proceedings of the 23rd Annual Conference of the European Association for Machine Translation",
month = jun,
year = "2022",
address = "Ghent, Belgium",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2022.eamt-1.31/",
pages = "283--284",
abstract = "This project aims to study the impact of adapting neural machine translation (NMT) systems through translation exemplars, determine the optimal similarity metric(s) for retrieving informative exemplars, and, verify the usefulness of this approach for domain adaptation of NMT systems."
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%0 Conference Proceedings %T Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars %A Tezcan, Arda %Y Moniz, Helena %Y Macken, Lieve %Y Rufener, Andrew %Y Barrault, Loïc %Y Costa-jussà, Marta R. %Y Declercq, Christophe %Y Koponen, Maarit %Y Kemp, Ellie %Y Pilos, Spyridon %Y Forcada, Mikel L. %Y Scarton, Carolina %Y Van den Bogaert, Joachim %Y Daems, Joke %Y Tezcan, Arda %Y Vanroy, Bram %Y Fonteyne, Margot %S Proceedings of the 23rd Annual Conference of the European Association for Machine Translation %D 2022 %8 June %I European Association for Machine Translation %C Ghent, Belgium %F tezcan-2022-dynamic %X This project aims to study the impact of adapting neural machine translation (NMT) systems through translation exemplars, determine the optimal similarity metric(s) for retrieving informative exemplars, and, verify the usefulness of this approach for domain adaptation of NMT systems. %U https://aclanthology.org/2022.eamt-1.31/ %P 283-284
Markdown (Informal)
[Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars](https://aclanthology.org/2022.eamt-1.31/) (Tezcan, EAMT 2022)
- Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars (Tezcan, EAMT 2022)
ACL
- Arda Tezcan. 2022. Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 283–284, Ghent, Belgium. European Association for Machine Translation.