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incurring only 1.63% reduction in validation accuracy. Moreover, SWAT reduces memory footprint during the backward pass by 23% to 50% for activations and 50% to 90% for weights. Sparse Activation allows for a best-of-both-worlds scenario. Adding a lot of parameters allows our model to learn more