@inproceedings{mukherjee-shrivastava-2023-mee4,
    title = "{MEE}4 and {XL}sim : {IIIT} {HYD}`s Submissions' for {WMT}23 Metrics Shared Task",
    author = "Mukherjee, Ananya  and
      Shrivastava, Manish",
    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/jlcl-multiple-ingestion/2023.wmt-1.66/",
    doi = "10.18653/v1/2023.wmt-1.66",
    pages = "800--805",
    abstract = "This paper presents our contributions to the WMT2023 shared metrics task, consisting of two distinct evaluation approaches: a) Unsupervised Metric (MEE4) and b) Supervised Metric (XLSim). MEE4 represents an unsupervised, reference-based assessment metric that quantifies linguistic features, encompassing lexical, syntactic, semantic, morphological, and contextual similarities, leveraging embeddings. In contrast, XLsim is a supervised reference-based evaluation metric, employing a Siamese Architecture, which regresses on Direct Assessments (DA) from previous WMT News Translation shared tasks from 2017-2022. XLsim is trained using XLM-RoBERTa (base) on English-German reference and mt pairs with human scores."
}