“…Recently, there is an increased interest on applying data augmentation techniques on sentence-level and sentence-pair natural language processing (NLP) tasks, such as text classification (Wei and Zou, 2019;Xie et al, 2019), natural language inference (Min et al, 2020) and machine translation . Augmentation methods explored for these tasks either create augmented instances by manipulating a few words in the original instance, such as word replacement (Zhang et al, 2015;Wang and Yang, 2015;Cai et al, 2020), random deletion (Wei and Zou, 2019), or word position swap (Ş ahin and Steedman, 2018;Min et al, 2020); or create entirely artificial instances via generative models, such as variational auto encoders (Yoo et al, 2019;Mesbah et al, 2019) or back-translation models (Yu et al, 2018;Iyyer et al, 2018).…”