@inproceedings{ou-li-2020-ynu,
    title = "{YNU}-oxz at {S}em{E}val-2020 Task 4: Commonsense Validation Using {BERT} with Bidirectional {GRU}",
    author = "Ou, Xiaozhi  and
      Li, Hongling",
    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-1.80/",
    doi = "10.18653/v1/2020.semeval-1.80",
    pages = "626--632",
    abstract = "This paper describes the system and results of our team participated in SemEval-2020 Task4: Commonsense Validation and Explanation (ComVE), which aim to distinguish meaningful natural language statements from unreasonable natural language statements. This task contains three subtasks: Subtask A{--}Validation, Subtask B{--}Explanation (Multi-Choice), and Subtask C{--} Explanation (Generation). In these three subtasks, we only participated in Subtask A, which aims to distinguish whether a given two natural language statements with similar wording are meaningful. To solve this problem, we proposed a method using a combination of BERT with the Bidirectional Gated Recurrent Unit (Bi-GRU). Our model achieved an accuracy of 0.836 in Subtask A (ranked 27/45)."
}