@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://preview.aclanthology.org/add-emnlp-2024-awards/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."
}