@inproceedings{li-etal-2023-lotus,
    title = "Lotus at {W}ojood{NER} Shared Task: Multilingual Transformers: Unveiling Flat and Nested Entity Recognition",
    author = "Li, Jiyong  and
      Azizov, Dilshod  and
      AlQuabeh, Hilal  and
      Liang, Shangsong",
    editor = "Sawaf, Hassan  and
      El-Beltagy, Samhaa  and
      Zaghouani, Wajdi  and
      Magdy, Walid  and
      Abdelali, Ahmed  and
      Tomeh, Nadi  and
      Abu Farha, Ibrahim  and
      Habash, Nizar  and
      Khalifa, Salam  and
      Keleg, Amr  and
      Haddad, Hatem  and
      Zitouni, Imed  and
      Mrini, Khalil  and
      Almatham, Rawan",
    booktitle = "Proceedings of ArabicNLP 2023",
    month = dec,
    year = "2023",
    address = "Singapore (Hybrid)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Author-page-Marten-During-lu/2023.arabicnlp-1.85/",
    doi = "10.18653/v1/2023.arabicnlp-1.85",
    pages = "765--770",
    abstract = "We introduce our systems developed for two subtasks in the shared task {\textquotedblleft}Wojood{\textquotedblright} on Arabic NER detection, part of ArabicNLP 2023. For Subtask 1, we employ the XLM-R model to predict Flat NER labels for given tokens using a single classifier capable of categorizing all labels. For Subtask 2, we use the XLM-R encoder by building 21 individual classifiers. Each classifier corresponds to a specific label and is designed to determine the presence of its respective label. In terms of performance, our systems achieved competitive \textit{micro-F1} scores of \textbf{0.83} for Subtask 1 and \textbf{0.76} for Subtask 2, according to the leaderboard scores."
}