@inproceedings{brassard-etal-2018-takelab,
    title = "{T}ake{L}ab at {S}em{E}val-2018 Task12: Argument Reasoning Comprehension with Skip-Thought Vectors",
    author = "Brassard, Ana  and
      Kuculo, Tin  and
      Boltu{\v{z}}i{\'c}, Filip  and
      {\v{S}}najder, Jan",
    editor = "Apidianaki, Marianna  and
      Mohammad, Saif M.  and
      May, Jonathan  and
      Shutova, Ekaterina  and
      Bethard, Steven  and
      Carpuat, Marine",
    booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/S18-1192/",
    doi = "10.18653/v1/S18-1192",
    pages = "1133--1136",
    abstract = "This paper describes our system for the SemEval-2018 Task 12: Argument Reasoning Comprehension Task. We utilize skip-thought vectors, sentence-level distributional vectors inspired by the popular word embeddings and the skip-gram model. We encode preprocessed sentences from the dataset into vectors, then perform a binary supervised classification of the warrant that justifies the use of the reason as support for the claim. We explore a few variations of the model, reaching 54.1{\%} accuracy on the test set, which placed us 16th out of 22 teams participating in the task."
}