@inproceedings{smiley-etal-2018-e2e,
    title = "The {E}2{E} {NLG} Challenge: A Tale of Two Systems",
    author = "Smiley, Charese  and
      Davoodi, Elnaz  and
      Song, Dezhao  and
      Schilder, Frank",
    editor = "Krahmer, Emiel  and
      Gatt, Albert  and
      Goudbeek, Martijn",
    booktitle = "Proceedings of the 11th International Conference on Natural Language Generation",
    month = nov,
    year = "2018",
    address = "Tilburg University, The Netherlands",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W18-6558/",
    doi = "10.18653/v1/W18-6558",
    pages = "472--477",
    abstract = "This paper presents the two systems we entered into the 2017 E2E NLG Challenge: TemplGen, a templated-based system and SeqGen, a neural network-based system. Through the automatic evaluation, SeqGen achieved competitive results compared to the template-based approach and to other participating systems as well. In addition to the automatic evaluation, in this paper we present and discuss the human evaluation results of our two systems."
}