@inproceedings{bozdag-etal-2023-arizonans,
    title = "Arizonans at {S}em{E}val-2023 Task 9: Multilingual Tweet Intimacy Analysis with {XLM}-{T}",
    author = "Bozdag, Nimet Beyza  and
      Bilgis, Tugay  and
      Bethard, Steven",
    editor = {Ojha, Atul Kr.  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Da San Martino, Giovanni  and
      Tayyar Madabushi, Harish  and
      Kumar, Ritesh  and
      Sartori, Elisa},
    booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.semeval-1.230",
    doi = "10.18653/v1/2023.semeval-1.230",
    pages = "1656--1659",
    abstract = "This paper presents the systems and approaches of the Arizonans team for the SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis. We finetune the Multilingual RoBERTa model trained with about 200M tweets, XLM-T. Our final model ranked 9th out of 45 overall, 13th in seen languages, and 8th in unseen languages.",
}

This paper presents the systems and approaches of the Arizonans team for the SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis. We finetune the Multilingual RoBERTa model trained with about 200M tweets, XLM-T. Our final model ranked 9th out of 45 overall, 13th in seen languages, and 8th in unseen languages.
Bozdag, Nimet Beyza Bilgis, Tugay Bethard, Steven
Arizonans at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis with XLM-T