This finding also agrees with the observation  we found in multi-label classification: our approach has superior generalization capability in low-resource setting with few training examples.
to the strongest baseline HD-LSTM with 34.51M and 0.03 seconds for one batch, our approach has 17.84M parameters and takes 0.06 seconds in an acceleration setting, and 0.12 seconds without acceleration.