@inproceedings{singh-etal-2020-copynext,
    title = "{C}opy{N}ext: Explicit Span Copying and Alignment in Sequence to Sequence Models",
    author = "Singh, Abhinav  and
      Xia, Patrick  and
      Qin, Guanghui  and
      Yarmohammadi, Mahsa  and
      Van Durme, Benjamin",
    editor = "Agrawal, Priyanka  and
      Kozareva, Zornitsa  and
      Kreutzer, Julia  and
      Lampouras, Gerasimos  and
      Martins, Andr\'e  and
      Ravi, Sujith  and
      Vlachos, Andreas",
    booktitle = "Proceedings of the Fourth Workshop on Structured Prediction for NLP",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/build-pipeline-with-new-library/2020.spnlp-1.2/",
    doi = "10.18653/v1/2020.spnlp-1.2",
    pages = "11--16",
    abstract = "Copy mechanisms are employed in sequence to sequence (seq2seq) models to generate reproductions of words from the input to the output. These frameworks, operating at the lexical type level, fail to provide an explicit alignment that records where each token was copied from. Further, they require contiguous token sequences from the input (spans) to be copied individually. We present a model with an explicit token-level copy operation and extend it to copying entire spans. Our model provides hard alignments between spans in the input and output, allowing for nontraditional applications of seq2seq, like information extraction. We demonstrate the approach on Nested Named Entity Recognition, achieving near state-of-the-art accuracy with an order of magnitude increase in decoding speed."
}