@inproceedings{koto-etal-2022-cloze,
    title = "Cloze Evaluation for Deeper Understanding of Commonsense Stories in {I}ndonesian",
    author = "Koto, Fajri  and
      Baldwin, Timothy  and
      Lau, Jey Han",
    editor = "Bosselut, Antoine  and
      Li, Xiang  and
      Lin, Bill Yuchen  and
      Shwartz, Vered  and
      Majumder, Bodhisattwa Prasad  and
      Lal, Yash Kumar  and
      Rudinger, Rachel  and
      Ren, Xiang  and
      Tandon, Niket  and
      Zouhar, Vil{\'e}m",
    booktitle = "Proceedings of the First Workshop on Commonsense Representation and Reasoning (CSRR 2022)",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.csrr-1.2",
    doi = "10.18653/v1/2022.csrr-1.2",
    pages = "8--16",
    abstract = "Story comprehension that involves complex causal and temporal relations is a critical task in NLP, but previous studies have focused predominantly on English, leaving open the question of how the findings generalize to other languages, such as Indonesian. In this paper, we follow the Story Cloze Test framework of Mostafazadeh et al. (2016) in evaluating story understanding in Indonesian, by constructing a four-sentence story with one correct ending and one incorrect ending. To investigate commonsense knowledge acquisition in language models, we experimented with: (1) a classification task to predict the correct ending; and (2) a generation task to complete the story with a single sentence. We investigate these tasks in two settings: (i) monolingual training and ii) zero-shot cross-lingual transfer between Indonesian and English.",
}