@inproceedings{tomasulo-etal-2020-ynu,
    title = "{YNU}-{HPCC} at {S}em{E}val-2020 Task 7: Using an Ensemble {B}i{GRU} Model to Evaluate the Humor of Edited News Titles",
    author = "Tomasulo, Joseph  and
      Wang, Jin  and
      Zhang, Xuejie",
    editor = "Herbelot, Aurelie  and
      Zhu, Xiaodan  and
      Palmer, Alexis  and
      Schneider, Nathan  and
      May, Jonathan  and
      Shutova, Ekaterina",
    booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
    month = dec,
    year = "2020",
    address = "Barcelona (online)",
    publisher = "International Committee for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2020.semeval-1.110/",
    doi = "10.18653/v1/2020.semeval-1.110",
    pages = "871--875",
    abstract = "This paper describes an ensemble model designed for Semeval-2020 Task 7. The task is based on the Humicroedit dataset that is comprised of news titles and one-word substitutions designed to make them humorous. We use BERT, FastText, Elmo, and Word2Vec to encode these titles then pass them to a bidirectional gated recurrent unit (BiGRU) with attention. Finally, we used XGBoost on the concatenation of the results of the different models to make predictions."
}