@inproceedings{brooks-youssef-2021-got,
    title = "{GOT}: Testing for Originality in Natural Language Generation",
    author = "Brooks, Jennifer  and
      Youssef, Abdou",
    editor = "Bosselut, Antoine  and
      Durmus, Esin  and
      Gangal, Varun Prashant  and
      Gehrmann, Sebastian  and
      Jernite, Yacine  and
      Perez-Beltrachini, Laura  and
      Shaikh, Samira  and
      Xu, Wei",
    booktitle = "Proceedings of the First Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2021.gem-1.7/",
    doi = "10.18653/v1/2021.gem-1.7",
    pages = "68--72",
    abstract = "We propose an approach to automatically test for originality in generation tasks where no standard automatic measures exist. Our proposal addresses original uses of language, not necessarily original ideas. We provide an algorithm for our approach and a run-time analysis. The algorithm, which finds all of the original fragments in a ground-truth corpus and can reveal whether a generated fragment copies an original without attribution, has a run-time complexity of theta(nlogn) where n is the number of sentences in the ground truth."
}