@inproceedings{herrmann-krebs-2022-felix,
    title = "Felix{\&}Julia at {S}em{E}val-2022 Task 4: Patronizing and Condescending Language Detection",
    author = "Herrmann, Felix  and
      Krebs, Julia",
    editor = "Emerson, Guy  and
      Schluter, Natalie  and
      Stanovsky, Gabriel  and
      Kumar, Ritesh  and
      Palmer, Alexis  and
      Schneider, Nathan  and
      Singh, Siddharth  and
      Ratan, Shyam",
    booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
    month = jul,
    year = "2022",
    address = "Seattle, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.semeval-1.46/",
    doi = "10.18653/v1/2022.semeval-1.46",
    pages = "357--362",
    abstract = "This paper describes the authors' submission to the SemEval-2022 task 4: Patronizing and Condescending Language (PCL) Detection. The aim of the task is the detection and classification of PCL in an annotated dataset. Subtask 1 includes a binary classification task (PCL or not PCL). Subtask 2 is a multi label classification task where the system identifies different categories of PCL. The authors of this paper submitted two different models: one RoBERTa model and one DistilBERT model. Both systems performed better than the random and RoBERTA baseline given by the task organizers. The RoBERTA model finetuned by the authors performed better in both subtasks than the DistilBERT model."
}