larger it has more parameters it can learn more about the data together with the noise it can probably be a more robust and that's what makes it generalized better and we'll also see as we see here it's more robust to these transformations and it's also going to be more robust to adversarial perturbations so the the technique again is uh illustrated here as as we said it's pretty simple first so step one step one train the teacher model with label data as you would step two you infer the pseudo labels on unlabeled data step three