@inproceedings{dreano-etal-2023-embed,
    title = "{E}mbed{\_}{L}lama: Using {LLM} Embeddings for the Metrics Shared Task",
    author = {Dreano, S{\"o}ren  and
      Molloy, Derek  and
      Murphy, Noel},
    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-1.60/",
    doi = "10.18653/v1/2023.wmt-1.60",
    pages = "738--745",
    abstract = "Embed{\_}llama is an assessment metric for language translation that hinges upon the utilization of the recently introduced Llama 2 Large Language Model (LLM), specifically, focusing on its embedding layer, with the aim of transforming sentences into a vector space that establishes connections between geometric and semantic proximities"
}