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cs.CL2024
SoftEDA: Rethinking Rule-Based Data Augmentation with Soft Labels
Juhwan Choi, Kyohoon Jin, Junho Lee +2
Rule-based text data augmentation is widely used for NLP tasks due to its simplicity. However, this method can potentially damage the original meaning of the text, ultimately hurti…
cs.CL2024
AutoAugment Is What You Need: Enhancing Rule-based Augmentation Methods in Low-resource Regimes
Juhwan Choi, Kyohoon Jin, Junho Lee +2
Text data augmentation is a complex problem due to the discrete nature of sentences. Although rule-based augmentation methods are widely adopted in real-world applications because…
cs.CL2024★ 1 cited
GPTs Are Multilingual Annotators for Sequence Generation Tasks
Juhwan Choi, Eunju Lee, Kyohoon Jin +1
Data annotation is an essential step for constructing new datasets. However, the conventional approach of data annotation through crowdsourcing is both time-consuming and expensive…