This continuous space representation approach has shown better results compared to lexical matching approaches (e.g., word-alignment models).
for two sequences S l = (w 1 , w 2 , ..., w n ) and S r = (w 1 , w 2 , ..., w m ), we add " S " and " E " to the head and tail of them respectively to form an input S l and S r of the network.