@inproceedings{socha-2020-ks,
    title = "{KS}@{LTH} at {S}em{E}val-2020 Task 12: Fine-tuning Multi- and Monolingual Transformer Models for Offensive Language Detection",
    author = "Socha, Kasper",
    editor = "Herbelot, Aurelie  and
      Zhu, Xiaodan  and
      Palmer, Alexis  and
      Schneider, Nathan  and
      May, Jonathan  and
      Shutova, Ekaterina",
    booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
    month = dec,
    year = "2020",
    address = "Barcelona (online)",
    publisher = "International Committee for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2020.semeval-1.270/",
    doi = "10.18653/v1/2020.semeval-1.270",
    pages = "2045--2053",
    abstract = "This paper describes the KS@LTH system for SemEval-2020 Task 12 OffensEval2: Multilingual Offensive Language Identification in Social Media. We compare mono- and multilingual models based on fine-tuning pre-trained transformer models for offensive language identification in Arabic, Greek, English and Turkish. For Danish, we explore the possibility of fine-tuning a model pre-trained on a similar language, Swedish, and additionally also cross-lingual training together with English."
}