and that noise can be on the data or in the model itself and here also the unlabeled images that you have labeled with the teacher you do the exact same thing so you train on both of these data sets and step four is if you want to do iterative training use the student as a teacher and go back to step two now they have uh some more tricks when they do this iterative training they are also up the batch size during the iterative training and so on so they do a lot of things to make the student learn something more something better than the