SAPPHIRE

الياقوت: مقاربات لتوليد مفهوم إلى نص محسّن

رمز SAPPHIRE: مقاربات لتوليد مفهوم إلى نص محسّن منشور في INLG 2021 (أفضل ورقة طويلة). يمكنك الاستشهاد بها على النحو التالي:

 @inproceedings{feng-etal-2021-sapphire,
    title = "{SAPPHIRE}: Approaches for Enhanced Concept-to-Text Generation",
    author = "Feng, Steven Y.  and
      Huynh, Jessica  and
      Narisetty, Chaitanya Prasad  and
      Hovy, Eduard  and
      Gangal, Varun",
    booktitle = "Proceedings of the 14th International Conference on Natural Language Generation",
    month = aug,
    year = "2021",
    address = "Aberdeen, Scotland, UK",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.inlg-1.21",
    pages = "212--225",
    abstract = "We motivate and propose a suite of simple but effective improvements for concept-to-text generation called SAPPHIRE: Set Augmentation and Post-hoc PHrase Infilling and REcombination. We demonstrate their effectiveness on generative commonsense reasoning, a.k.a. the CommonGen task, through experiments using both BART and T5 models. Through extensive automatic and human evaluation, we show that SAPPHIRE noticeably improves model performance. An in-depth qualitative analysis illustrates that SAPPHIRE effectively addresses many issues of the baseline model generations, including lack of commonsense, insufficient specificity, and poor fluency.",
}

المؤلفون: ستيفن ي. فنغ ، جيسيكا هوينه ، شيتانيا براساد ناريتي ، إدوارد هوفي ، فارون جانجال

يمكن العثور على ملصق وموارد أخرى هنا .

ملاحظة: يجب توجيه الاستفسارات إلى [email protected] أو عن طريق فتح مشكلة هنا.

سيتم إصدار الرمز قريبًا