Compared with the auxiliary task, which focuses on learning transferable word features based on the downward dependency relations, cDAN works in the other direction and further improves the transferability of the model when combining with the auxiliary module.
these two transferable modules aim at learning syntactically sensitive word representations that are transferable across domains.