semi-square learning had a background just the dream is to make sure that unlabeled data improves the performance of supervised learning or label data even when you have a lot of labels and that's what this paper tries to achieve so you you already remember how unfiltered aft was not able to give sufficient gain on imagenet for the UDA paper and they actually use clever filtering techniques noisy student is actually a larger scale version of that so the way it works is as follows you train a teacher model with long label