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harles
544 days ago
That could explain compute efficiency, but has nothing to do with the parameter efficiency pointed at in the paper.
1 comments
vlovich123
543 days ago
Haven’t read the paper but my guess around that is that the same reason sparse attention networks (where they 0 out many weights) just have the sparse tensors be larger.
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mayukhdeb
542 days ago
In this paper, we don't zero out the weights. We remove them.
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vlovich123
541 days ago
Thanks for the correction! Can it be retrofitted into existing models through distillation or do you have to train the model from scratch?
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