Before revision:  We find that certain examples , which we term pruning identified exemplars (PIEs) , and classes are systematically more impacted by the introduction of sparsity.
After revision:  We find that models with radically different numbers of weights have comparable top-line performance metrics but diverge considerably in behavior on a narrow subset of the dataset. This small subset of data points , which we term pruning identified exemplars (PIEs) , and classes are systematically more impacted by the introduction of sparsity.