@inproceedings{tiedemann-de-gibert-2023-opus,
title = "The {OPUS}-{MT} Dashboard {--} A Toolkit for a Systematic Evaluation of Open Machine Translation Models",
author = {Tiedemann, J{\"o}rg and
de Gibert, Ona},
editor = "Bollegala, Danushka and
Huang, Ruihong and
Ritter, Alan",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-demo.30",
doi = "10.18653/v1/2023.acl-demo.30",
pages = "315--327",
abstract = "The OPUS-MT dashboard is a web-based platform that provides a comprehensive overview of open translation models. We focus on a systematic collection of benchmark results with verifiable translation performance and large coverage in terms of languages and domains. We provide results for in-house OPUS-MT and Tatoeba models as well as external models from the Huggingface repository and user-contributed translations. The functionalities of the evaluation tool include summaries of benchmarks for over 2,300 models covering 4,560 language directions and 294 languages, as well as the inspection of predicted translations against their human reference. We focus on centralization, reproducibility and coverage of MT evaluation combined with scalability. The dashboard can be accessed live at \url{https://opus.nlpl.eu/dashboard/}.",
}
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%0 Conference Proceedings
%T The OPUS-MT Dashboard – A Toolkit for a Systematic Evaluation of Open Machine Translation Models
%A Tiedemann, Jörg
%A de Gibert, Ona
%Y Bollegala, Danushka
%Y Huang, Ruihong
%Y Ritter, Alan
%S Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F tiedemann-de-gibert-2023-opus
%X The OPUS-MT dashboard is a web-based platform that provides a comprehensive overview of open translation models. We focus on a systematic collection of benchmark results with verifiable translation performance and large coverage in terms of languages and domains. We provide results for in-house OPUS-MT and Tatoeba models as well as external models from the Huggingface repository and user-contributed translations. The functionalities of the evaluation tool include summaries of benchmarks for over 2,300 models covering 4,560 language directions and 294 languages, as well as the inspection of predicted translations against their human reference. We focus on centralization, reproducibility and coverage of MT evaluation combined with scalability. The dashboard can be accessed live at https://opus.nlpl.eu/dashboard/.
%R 10.18653/v1/2023.acl-demo.30
%U https://aclanthology.org/2023.acl-demo.30
%U https://doi.org/10.18653/v1/2023.acl-demo.30
%P 315-327
Markdown (Informal)
[The OPUS-MT Dashboard – A Toolkit for a Systematic Evaluation of Open Machine Translation Models](https://aclanthology.org/2023.acl-demo.30) (Tiedemann & de Gibert, ACL 2023)
ACL