Before revision:  Results on the classic text classification task ( 24 datasets in various sizes and domains ) show that our approaches achieve superior performance while preserving higher efficiency in computation over the vanilla Transformer and previous depth-adaptive models.
After revision:  Results on the classic text classification task with 24 datasets in various sizes and domains ) show that our approaches achieve superior performance while preserving higher efficiency in computation over the vanilla Transformer and previous depth-adaptive models.