@inproceedings{ramesh-kashyap-kan-2020-sciwing,
    title = "{S}ci{WING}{--} A Software Toolkit for Scientific Document Processing",
    author = "Ramesh Kashyap, Abhinav  and
      Kan, Min-Yen",
    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/jlcl-multiple-ingestion/2020.sdp-1.13/",
    doi = "10.18653/v1/2020.sdp-1.13",
    pages = "113--120",
    abstract = "We introduce SciWING, an open-source soft-ware toolkit which provides access to state-of-the-art pre-trained models for scientific document processing (SDP) tasks, such as citation string parsing, logical structure recovery and citation intent classification. Compared to other toolkits, SciWING follows a full neural pipeline and provides a Python inter-face for SDP. When needed, SciWING provides fine-grained control for rapid experimentation with different models by swapping and stacking different modules. Transfer learning from general and scientific documents specific pre-trained transformers (i.e., BERT, SciBERT, etc.) can be performed. SciWING incorporates ready-to-use web and terminal-based applications and demonstrations to aid adoption and development. The toolkit is available from \url{http://sciwing.io} and the demos are available at \url{http://rebrand.ly/sciwing-demo}."
}