@inproceedings{maillard-etal-2024-findings,
title = "Findings of the {WMT} 2024 Shared Task of the Open Language Data Initiative",
author = "Maillard, Jean and
Burchell, Laurie and
Anastasopoulos, Antonios and
Federmann, Christian and
Koehn, Philipp and
Wang, Skyler",
editor = "Haddow, Barry and
Kocmi, Tom and
Koehn, Philipp and
Monz, Christof",
booktitle = "Proceedings of the Ninth Conference on Machine Translation",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.wmt-1.4",
pages = "110--117",
abstract = "We present the results of the WMT 2024 shared task of the Open Language Data Initiative. Participants were invited to contribute to the FLORES+ and MT Seed multilingual datasets, two foundational open resources that facilitate the organic expansion of language technology{'}s reach. We accepted ten submissions covering 16 languages, which extended the range of languages included in the datasets and improved the quality of existing data.",
}
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<abstract>We present the results of the WMT 2024 shared task of the Open Language Data Initiative. Participants were invited to contribute to the FLORES+ and MT Seed multilingual datasets, two foundational open resources that facilitate the organic expansion of language technology’s reach. We accepted ten submissions covering 16 languages, which extended the range of languages included in the datasets and improved the quality of existing data.</abstract>
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%0 Conference Proceedings
%T Findings of the WMT 2024 Shared Task of the Open Language Data Initiative
%A Maillard, Jean
%A Burchell, Laurie
%A Anastasopoulos, Antonios
%A Federmann, Christian
%A Koehn, Philipp
%A Wang, Skyler
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Koehn, Philipp
%Y Monz, Christof
%S Proceedings of the Ninth Conference on Machine Translation
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F maillard-etal-2024-findings
%X We present the results of the WMT 2024 shared task of the Open Language Data Initiative. Participants were invited to contribute to the FLORES+ and MT Seed multilingual datasets, two foundational open resources that facilitate the organic expansion of language technology’s reach. We accepted ten submissions covering 16 languages, which extended the range of languages included in the datasets and improved the quality of existing data.
%U https://aclanthology.org/2024.wmt-1.4
%P 110-117
Markdown (Informal)
[Findings of the WMT 2024 Shared Task of the Open Language Data Initiative](https://aclanthology.org/2024.wmt-1.4) (Maillard et al., WMT 2024)
ACL