To better describe our framework, we summarize the training procedure of our framework 848 in Algorithm 1.
we first individually train the initial in-domain and out-of-domain NMT models, respectively denoted by θ in and θ 0out , via minimizing the negative likelihood of their own training corpora D in and D out (Line 3): Then, we iteratively perform bidirectional translation knowledge transfer to update both in-domain and out-of-domain NMT models, until the maximal iteration number K is reached (Lines 5-14).