@inproceedings{sung-etal-2020-clac,
    title = "{CL}a{C} at {S}em{E}val-2020 Task 5: Muli-task Stacked {B}i-{LSTM}s",
    author = "Sung, MinGyou  and
      Bagherzadeh, Parsa  and
      Bergler, Sabine",
    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-1.54/",
    doi = "10.18653/v1/2020.semeval-1.54",
    pages = "445--450",
    abstract = "We consider detection of the span of antecedents and consequents in argumentative prose a structural, grammatical task. Our system comprises a set of stacked Bi-LSTMs trained on two complementary linguistic annotations. We explore the effectiveness of grammatical features (POS and clause type) through ablation. The reported experiments suggest that a multi-task learning approach using this external, grammatical knowledge is useful for detecting the extent of antecedents and consequents and performs nearly as well without the use of word embeddings."
}