More specifically, at the k-th iteration, we first transfer the translation knowledge of the previous in-domain NMT model θ out trained on D out (Line 6), and then reversely transfer the translation knowledge encoded by θ Obviously, during the above procedure, one of important steps is how to transfer the translation knowledge from one domain-specific NMT model to the other one.
if we directly employ conventional domain transfer approaches, such as fine-tuning, as the iterative dual domain adaptation proceeds, the previously learned translation knowledge tends to be ignored.