BriefGPT.xyz
Feb, 2024
AutoAugment是您所需的：增强基于规则的增强方法在低资源环境中的应用
AutoAugment Is What You Need: Enhancing Rule-based Augmentation Methods in Low-resource Regimes
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Juhwan Choi, Kyohoon Jin, Junho Lee, Sangmin Song, Youngbin Kim
TL;DR
本文提出了一种基于AutoAugment的方法来解决文本数据增强中的语义损害问题，并实验证明该方法可以改善现有的增强方法，并增强先进的预训练语言模型。
Abstract
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 of their simplicity, they suffer
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