@inproceedings{wang-etal-2018-co,
    title = "A Co-Matching Model for Multi-choice Reading Comprehension",
    author = "Wang, Shuohang  and
      Yu, Mo  and
      Jiang, Jing  and
      Chang, Shiyu",
    editor = "Gurevych, Iryna  and
      Miyao, Yusuke",
    booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/P18-2118/",
    doi = "10.18653/v1/P18-2118",
    pages = "746--751",
    abstract = "Multi-choice reading comprehension is a challenging task, which involves the matching between a passage and a question-answer pair. This paper proposes a new co-matching approach to this problem, which jointly models whether a passage can match both a question and a candidate answer. Experimental results on the RACE dataset demonstrate that our approach achieves state-of-the-art performance."
}