Pre-trained Data Augmentation for Text Classification

Author:

Queiroz Abonizio HugoORCID,Barbon Junior SylvioORCID

Publisher

Springer International Publishing

Reference33 articles.

1. Anaby-Tavor, A., et al.: Not enough data deep learning to the rescue. arXiv preprint arXiv:1911.03118 (2019)

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3. Cubuk, E.D., Zoph, B., Mane, D., Vasudevan, V., Le, Q.V.: Autoaugment: learning augmentation policies from data (2019).https://arxiv.org/pdf/1805.09501.pdf

4. Demšar, J.: Statistical comparisons of classifiers over multiple data sets. J. Mach. Learn. Res. 7, 1–30 (2006)

5. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Vol. 1 (Long and Short Papers), pp. 4171–4186. Association for Computational Linguistics, Minneapolis, Minnesota, June 2019. https://doi.org/10.18653/v1/N19-1423, https://www.aclweb.org/anthology/N19-1423

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