@inproceedings{xu-etal-2021-lisn,
title = "{LISN} @ {WMT} 2021",
author = "Xu, Jitao and
Pham, Minh Quang and
Abdul Rauf, Sadaf and
Yvon, Fran{\c{c}}ois",
booktitle = "Proceedings of the Sixth Conference on Machine Translation",
month = nov,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wmt-1.22",
pages = "232--242",
abstract = "This paper describes LISN{'}s submissions to two shared tasks at WMT{'}21. For the biomedical translation task, we have developed resource-heavy systems for the English-French language pair, using both out-of-domain and in-domain corpora. The target genre for this task (scientific abstracts) corresponds to texts that often have a standardized structure. Our systems attempt to take this structure into account using a hierarchical system of sentence-level tags. Translation systems were also prepared for the News task for the French-German language pair. The challenge was to perform unsupervised adaptation to the target domain (financial news). For this, we explored the potential of retrieval-based strategies, where sentences that are similar to test instances are used to prime the decoder.",
}
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<abstract>This paper describes LISN’s submissions to two shared tasks at WMT’21. For the biomedical translation task, we have developed resource-heavy systems for the English-French language pair, using both out-of-domain and in-domain corpora. The target genre for this task (scientific abstracts) corresponds to texts that often have a standardized structure. Our systems attempt to take this structure into account using a hierarchical system of sentence-level tags. Translation systems were also prepared for the News task for the French-German language pair. The challenge was to perform unsupervised adaptation to the target domain (financial news). For this, we explored the potential of retrieval-based strategies, where sentences that are similar to test instances are used to prime the decoder.</abstract>
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%0 Conference Proceedings
%T LISN @ WMT 2021
%A Xu, Jitao
%A Pham, Minh Quang
%A Abdul Rauf, Sadaf
%A Yvon, François
%S Proceedings of the Sixth Conference on Machine Translation
%D 2021
%8 nov
%I Association for Computational Linguistics
%C Online
%F xu-etal-2021-lisn
%X This paper describes LISN’s submissions to two shared tasks at WMT’21. For the biomedical translation task, we have developed resource-heavy systems for the English-French language pair, using both out-of-domain and in-domain corpora. The target genre for this task (scientific abstracts) corresponds to texts that often have a standardized structure. Our systems attempt to take this structure into account using a hierarchical system of sentence-level tags. Translation systems were also prepared for the News task for the French-German language pair. The challenge was to perform unsupervised adaptation to the target domain (financial news). For this, we explored the potential of retrieval-based strategies, where sentences that are similar to test instances are used to prime the decoder.
%U https://aclanthology.org/2021.wmt-1.22
%P 232-242
Markdown (Informal)
[LISN @ WMT 2021](https://aclanthology.org/2021.wmt-1.22) (Xu et al., WMT 2021)
ACL
- Jitao Xu, Minh Quang Pham, Sadaf Abdul Rauf, and François Yvon. 2021. LISN @ WMT 2021. In Proceedings of the Sixth Conference on Machine Translation, pages 232–242, Online. Association for Computational Linguistics.