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CATIE-AQ/e2e_nlg_french

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Declared licence: cc-by-sa-4.0, from the tagEvidence: README.md at 65afebe
Licence files: No licence file at the top level of the repositoryEvidence: file list at 65afebe
Declared sources: None listed in the card metadata
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Citation text from the card

@inproceedings{dusek-etal-2019-semantic,
    title = "Semantic Noise Matters for Neural Natural Language Generation",
    author = "Du{\v{s}}ek, Ond{\v{r}}ej  and
      Howcroft, David M.  and
      Rieser, Verena",
    editor = "van Deemter, Kees  and
      Lin, Chenghua  and
      Takamura, Hiroya",
    booktitle = "Proceedings of the 12th International Conference on Natural Language Generation",
    month = oct # "–" # nov,
    year = "2019",
    address = "Tokyo, Japan",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W19-8652/",
    doi = "10.18653/v1/W19-8652",
    pages = "421--426",
    abstract = "Neural natural language generation (NNLG) systems are known for their pathological outputs, i.e. generating text which is unrelated to the input specification. In this paper, we show the impact of semantic noise on state-of-the-art NNLG models which implement different semantic control mechanisms. We find that cleaned data can improve semantic correctness by up to 97{\%}, while maintaining fluency. We also find that the most common error is omitting information, rather than hallucination."
}

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dataset_licence({ "id": "CATIE-AQ/e2e_nlg_french" })
signal: "permissive"
stated_licence: "cc-by-sa-4.0"
sources: 0