Under the standard encoder-decoder architecture, an encoder first maps the source-language input sentence into a sequence of hidden vectors, and a decoder then incrementally predicts the target output sentence.
we should notice that several recent models (Vaswani et al., 2017;Zheng et al., 2017;Cheng et al., 2018) which have been shown to be more powerful can also serve as our baseline, since these models focus on very different aspects of NMT, which could be potentially complementary with our focus of syntax integration.