@inproceedings{shmalts-2023-john,
    title = "John Boy Walton at {S}em{E}val-2023 Task 5: An Ensemble Approach to Spoiler Classification and Retrieval for Clickbait Spoiling",
    author = "Shmalts, Maksim",
    editor = {Ojha, Atul Kr.  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Da San Martino, Giovanni  and
      Tayyar Madabushi, Harish  and
      Kumar, Ritesh  and
      Sartori, Elisa},
    booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest_wac_2008/2023.semeval-1.289/",
    doi = "10.18653/v1/2023.semeval-1.289",
    pages = "2100--2106",
    abstract = "Clickbait spoiling is a task of generating or retrieving a fairly short text with a purpose to satisfy curiosity of a content consumer without their addressing to the document linked to a clickbait post or headline. In this paper we introduce an ensemble approach to clickbait spoiling task at SemEval-2023. The tasks consists of spoiler classification and retrieval on Webis-Clickbait-22 dataset. We show that such an ensemble solution is quite successful at classification, whereas it might perform poorly at retrieval with no additional features. In conclusion we outline our thoughts on possible directions to improving the approach and shape a set of suggestions to the said features."
}