1 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.CL2021
SSMix: Saliency-Based Span Mixup for Text Classification
Soyoung Yoon, Gyuwan Kim, Kyumin Park
Data augmentation with mixup has shown to be effective on various computer vision tasks. Despite its great success, there has been a hurdle to apply mixup to NLP tasks since text c…
cs.CL2021★ 1 cited
Consistency Training with Virtual Adversarial Discrete Perturbation
Jungsoo Park, Gyuwan Kim, Jaewoo Kang
Consistency training regularizes a model by enforcing predictions of original and perturbed inputs to be similar. Previous studies have proposed various augmentation methods for th…
cs.CL2020★ 1 cited
Two-stage Textual Knowledge Distillation for End-to-End Spoken Language Understanding
Seongbin Kim, Gyuwan Kim, Seongjin Shin +1
End-to-end approaches open a new way for more accurate and efficient spoken language understanding (SLU) systems by alleviating the drawbacks of traditional pipeline systems. Previ…