Before revision:  Many augmentation techniques have been proposed to improve the performance of state-of-the-art (SOTA) systems in new domains that lack the necessary amount of data for training. However, these augmentation techniques (e.g. paraphrasing) also require some mediocre amount of data since they use learning-based approaches.
After revision:  Many augmentation techniques have been proposed to improve the performance of state-of-the-art (SOTA) systems in new domains . Up to now, these learning-based techniques (e.g. paraphrasing) also require some mediocre amount of data since they use learning-based approaches.