Self-supervised Regularization for Text Classification
AbstractText classification is a widely studied problem and has broad applications. In many real-world problems, the number of texts for training classification models is limited, which renders these models prone to overfitting. To address this problem, we propose SSL-Reg, a data-dep...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
The MIT Press
2021-01-01
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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_00389/102845/Self-supervised-Regularization-for-Text |