@inproceedings{lo-etal-2023-metric,
title = "Metric Score Landscape Challenge ({MSLC}23): Understanding Metrics{'} Performance on a Wider Landscape of Translation Quality",
author = "Lo, Chi-kiu and
Larkin, Samuel and
Knowles, Rebecca",
editor = "Koehn, Philipp and
Haddow, Barry and
Kocmi, Tom and
Monz, Christof",
booktitle = "Proceedings of the Eighth Conference on Machine Translation",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.wmt-1.65",
doi = "10.18653/v1/2023.wmt-1.65",
pages = "776--799",
abstract = "The Metric Score Landscape Challenge (MSLC23) dataset aims to gain insight into metric scores on a broader/wider landscape of machine translation (MT) quality. It provides a collection of low- to medium-quality MT output on the WMT23 general task test set. Together with the high quality systems submitted to the general task, this will enable better interpretation of metric scores across a range of different levels of translation quality. With this wider range of MT quality, we also visualize and analyze metric characteristics beyond just correlation.",
}
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%0 Conference Proceedings
%T Metric Score Landscape Challenge (MSLC23): Understanding Metrics’ Performance on a Wider Landscape of Translation Quality
%A Lo, Chi-kiu
%A Larkin, Samuel
%A Knowles, Rebecca
%Y Koehn, Philipp
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Monz, Christof
%S Proceedings of the Eighth Conference on Machine Translation
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F lo-etal-2023-metric
%X The Metric Score Landscape Challenge (MSLC23) dataset aims to gain insight into metric scores on a broader/wider landscape of machine translation (MT) quality. It provides a collection of low- to medium-quality MT output on the WMT23 general task test set. Together with the high quality systems submitted to the general task, this will enable better interpretation of metric scores across a range of different levels of translation quality. With this wider range of MT quality, we also visualize and analyze metric characteristics beyond just correlation.
%R 10.18653/v1/2023.wmt-1.65
%U https://aclanthology.org/2023.wmt-1.65
%U https://doi.org/10.18653/v1/2023.wmt-1.65
%P 776-799
Markdown (Informal)
[Metric Score Landscape Challenge (MSLC23): Understanding Metrics’ Performance on a Wider Landscape of Translation Quality](https://aclanthology.org/2023.wmt-1.65) (Lo et al., WMT 2023)
ACL