Thanks for the detailed answer!
I’ve seen this method used on a dataset where all the labels were known, and they simply used PS to increase the accuracy of their model. Maybe the deleted some labels on purpose? would that make sense?
Is PS only efficient when we’re missing labels in train/test/val?
If I understand this correctly, one should have very good accuracy to use this technique because the opposite would make the weights that make a wrong prediction stronger.