@inproceedings{zhang-abdul-mageed-2019-army,
    title = "No Army, No Navy: {BERT} Semi-Supervised Learning of {A}rabic Dialects",
    author = "Zhang, Chiyu  and
      Abdul-Mageed, Muhammad",
    editor = "El-Hajj, Wassim  and
      Belguith, Lamia Hadrich  and
      Bougares, Fethi  and
      Magdy, Walid  and
      Zitouni, Imed  and
      Tomeh, Nadi  and
      El-Haj, Mahmoud  and
      Zaghouani, Wajdi",
    booktitle = "Proceedings of the Fourth Arabic Natural Language Processing Workshop",
    month = aug,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/W19-4637/",
    doi = "10.18653/v1/W19-4637",
    pages = "279--284",
    abstract = "We present our deep leaning system submitted to MADAR shared task 2 focused on twitter user dialect identification. We develop tweet-level identification models based on GRUs and BERT in supervised and semi-supervised set-tings. We then introduce a simple, yet effective, method of porting tweet-level labels at the level of users. Our system ranks top 1 in the competition, with 71.70{\%} macro F1 score and 77.40{\%} accuracy."
}