@inproceedings{ferraro-suominen-2020-transformer,
    title = "Transformer Semantic Parsing",
    author = "Ferraro, Gabriela  and
      Suominen, Hanna",
    editor = "Kim, Maria  and
      Beck, Daniel  and
      Mistica, Meladel",
    booktitle = "Proceedings of the 18th Annual Workshop of the Australasian Language Technology Association",
    month = dec,
    year = "2020",
    address = "Virtual Workshop",
    publisher = "Australasian Language Technology Association",
    url = "https://preview.aclanthology.org/Add-Cong-Liu-Florida-Atlantic-University-author-id/2020.alta-1.16/",
    pages = "121--126",
    abstract = "In neural semantic parsing, sentences are mapped to meaning representations using encoder-decoder frameworks. In this paper, we propose to apply the Transformer architecture, instead of recurrent neural networks, to this task. Experiments in two data sets from different domains and with different levels of difficulty show that our model achieved better results than strong baselines in certain settings and competitive results across all our experiments."
}