@inproceedings{wan-huang-2020-kalm,
    title = "{K}a{LM} at {S}em{E}val-2020 Task 4: Knowledge-aware Language Models for Comprehension and Generation",
    author = "Wan, Jiajing  and
      Huang, Xinting",
    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/jlcl-multiple-ingestion/2020.semeval-1.67/",
    doi = "10.18653/v1/2020.semeval-1.67",
    pages = "543--550",
    abstract = "This paper presents our strategies in SemEval 2020 Task 4: Commonsense Validation and Explanation. We propose a novel way to search for evidence and choose the different large-scale pre-trained models as the backbone for three subtasks. The results show that our evidence-searching approach improves model performance on commonsense explanation task. Our team ranks 2nd in subtask C according to human evaluation score."
}