The correlation vector r L a,i will be fed to the GRL before the domain discriminator, which is used to predict the probability scores And meanwhile, the aspect attention weight α L a,i at the final hop serves as a selector to be a learnable alignment weight for each word.
the selective domain adversarial loss is a weighted crossentropy loss for all the words from the labeled source data D s and unlabeled target data D t : Existing studies (Yosinski et al., 2014;Mou et al., 2016) have already shown some evidence that lowlevel neural layer features (i.e., low-level task) are more easily transferred to different tasks or domains.