An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
AbstractNLP 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 applied to low-resource settings or novel tasks where significant time, money, or expertise is requir...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The MIT Press
2023-01-01
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| Series: | Transactions of the Association for Computational Linguistics |
| Online Access: | https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00542/115238/An-Empirical-Survey-of-Data-Augmentation-for |