An empirical survey of data augmentation for limited data learning in nlp
NLP has achieved great progress in the past decade through the use of neural models and
large labeled datasets. The dependence on abundant data prevents NLP models from being …
large labeled datasets. The dependence on abundant data prevents NLP models from being …
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
J Chen, D Tam, C Raffel, M Bansal… - Transactions of the …, 2023 - search.proquest.com
NLP has achieved great progress in the past decade through the use of neural models and
large labeled datasets. The dependence on abundant data prevents NLP models from being …
large labeled datasets. The dependence on abundant data prevents NLP models from being …
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
J Chen, D Tam, C Raffel, M Bansal… - Transactions of the …, 2023 - par.nsf.gov
NLP has achieved great progress in the past decade through the use of neural models and
large labeled datasets. The dependence on abundant data prevents NLP models from being …
large labeled datasets. The dependence on abundant data prevents NLP models from being …
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
J Chen, D Tam, C Raffel, M Bansal… - Transactions of the …, 2023 - transacl.org
NLP has achieved great progress in the past decade through the use of neural models and
large labeled datasets. The dependence on abundant data prevents NLP models from being …
large labeled datasets. The dependence on abundant data prevents NLP models from being …
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
J Chen, D Tam, C Raffel, M Bansal… - Transactions of the …, 2023 - aclanthology.org
NLP has achieved great progress in the past decade through the use of neural models and
large labeled datasets. The dependence on abundant data prevents NLP models from being …
large labeled datasets. The dependence on abundant data prevents NLP models from being …
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
J Chen, D Tam, C Raffel, M Bansal, D Yang - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
NLP has achieved great progress in the past decade through the use of neural models and
large labeled datasets. The dependence on abundant data prevents NLP models from being …
large labeled datasets. The dependence on abundant data prevents NLP models from being …
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
J Chen, D Tam, C Raffel, M Bansal, D Yang - arXiv preprint arXiv …, 2021 - arxiv.org
NLP has achieved great progress in the past decade through the use of neural models and
large labeled datasets. The dependence on abundant data prevents NLP models from being …
large labeled datasets. The dependence on abundant data prevents NLP models from being …
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
J Chen, D Tam, C Raffel, M Bansal… - Transactions of the …, 2023 - transacl.org
NLP has achieved great progress in the past decade through the use of neural models and
large labeled datasets. The dependence on abundant data prevents NLP models from being …
large labeled datasets. The dependence on abundant data prevents NLP models from being …