To this end, we propose an iterative dual domain adaptation framework for NMT.
we first pretrain in-domain and out-of-domain NMT models using their own training corpora respectively, and then iteratively perform bidirectional translation knowledge transfer (from indomain to out-of-domain and then vice versa) based on knowledge distillation until the indomain NMT model convergences.