@inproceedings{gidiotis-etal-2020-auth,
    title = "{AUTH} @ {CLS}ci{S}umm 20, {L}ay{S}umm 20, {L}ong{S}umm 20",
    author = "Gidiotis, Alexios  and
      Stefanidis, Stefanos  and
      Tsoumakas, Grigorios",
    editor = "Chandrasekaran, Muthu Kumar  and
      de Waard, Anita  and
      Feigenblat, Guy  and
      Freitag, Dayne  and
      Ghosal, Tirthankar  and
      Hovy, Eduard  and
      Knoth, Petr  and
      Konopnicki, David  and
      Mayr, Philipp  and
      Patton, Robert M.  and
      Shmueli-Scheuer, Michal",
    booktitle = "Proceedings of the First Workshop on Scholarly Document Processing",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2020.sdp-1.28/",
    doi = "10.18653/v1/2020.sdp-1.28",
    pages = "251--260",
    abstract = "We present the systems we submitted for the shared tasks of the Workshop on Scholarly Document Processing at EMNLP 2020. Our approaches to the tasks are focused on exploiting large Transformer models pre-trained on huge corpora and adapting them to the different shared tasks. For tasks 1A and 1B of CL-SciSumm we are using different variants of the BERT model to tackle the tasks of ``cited text span'' and ``facet'' identification. For the summarization tasks 2 of CL-SciSumm, LaySumm and LongSumm we make use of different variants of the PEGASUS model, with and without fine-tuning, adapted to the nuances of each one of those particular tasks."
}