@inproceedings{tziafas-etal-2021-fighting,
    title = "Fighting the {COVID}-19 Infodemic with a Holistic {BERT} Ensemble",
    author = "Tziafas, Georgios  and
      Kogkalidis, Konstantinos  and
      Caselli, Tommaso",
    editor = "Feldman, Anna  and
      Da San Martino, Giovanni  and
      Leberknight, Chris  and
      Nakov, Preslav",
    booktitle = "Proceedings of the Fourth Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2021.nlp4if-1.18/",
    doi = "10.18653/v1/2021.nlp4if-1.18",
    pages = "119--124",
    abstract = "This paper describes the TOKOFOU system, an ensemble model for misinformation detection tasks based on six different transformer-based pre-trained encoders, implemented in the context of the COVID-19 Infodemic Shared Task for English. We fine tune each model on each of the task`s questions and aggregate their prediction scores using a majority voting approach. TOKOFOU obtains an overall F1 score of 89.7{\%}, ranking first."
}