To speed up convergence, we initialize our model through pre-training the reading network and the generation network.
∀(T i , B i , C i ) ∈ D, we construct an artificial span setS i , and learn the parameters of the two networks by maximizing the following objective: S i is established in two steps: first, we collect all associated comments for (T i , B i ), extract n-grams (1 ≤ n ≤ 6) from the comments, and recognize an n-gram in B i as a salient span if it exactly matches with one of the n-grams of the comments.