半监督文本分类对抗训练方法
对从业者而言,该技术可显著降低对海量标注数据的依赖,提升实际场景中低资源分类任务的效果。
本文提出一种结合对抗训练的虚拟对抗训练方法(VAT),通过对抗性扰动增强模型对输入微扰的鲁棒性,在仅有少量标注数据的情况下显著提升文本分类性能。该方法将半监督学习与对抗训练结合,利用了无标注数据的潜在信息。
This report is categorized under AITOP's "Papers" desk. Key entities and technical topics under continuous tracking include adversarial-training, semi-supervised, text-classification, vat.
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