@inproceedings{alkhamissi-diab-2022-meta,
    title = "Meta {AI} at {A}rabic Hate Speech 2022: {M}ulti{T}ask Learning with Self-Correction for Hate Speech Classification",
    author = "AlKhamissi, Badr  and
      Diab, Mona",
    editor = "Al-Khalifa, Hend  and
      Elsayed, Tamer  and
      Mubarak, Hamdy  and
      Al-Thubaity, Abdulmohsen  and
      Magdy, Walid  and
      Darwish, Kareem",
    booktitle = "Proceedinsg of the 5th Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur`an QA and Fine-Grained Hate Speech Detection",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2022.osact-1.24/",
    pages = "186--193",
    abstract = "In this paper, we tackle the Arabic Fine-Grained Hate Speech Detection shared task and demonstrate significant improvements over reported baselines for its three subtasks. The tasks are to predict if a tweet contains (1) Offensive language; and whether it is considered (2) Hate Speech or not and if so, then predict the (3) Fine-Grained Hate Speech label from one of six categories. Our final solution is an ensemble of models that employs multitask learning and a self-consistency correction method yielding 82.7{\%} on the hate speech subtask{---}reflecting a 3.4{\%} relative improvement compared to previous work."
}