A little goes a long way: Improving toxic language classification despite data scarcity (2020.findings-emnlp)
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| Challenge: | Existing methods for toxic language classification have not been thoroughly explored. |
| Approach: | They propose to use data augmentation to generate new synthetic data from labeled seed datasets to improve toxic language classification. |
| Outcome: | The proposed techniques perform well on very scarce toxic language datasets while performing worse on shallower models. |
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DAGA: Data Augmentation with a Generation Approach for Low-resource Tagging Tasks (2020.emnlp-main)
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Bosheng Ding, Linlin Liu, Lidong Bing, Canasai Kruengkrai, Thien Hai Nguyen, Shafiq Joty, Luo Si, Chunyan Miao
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