Before revision:  Unlike NMT, the attention-aware inference of NAS requires the prediction of the optimal attention distribution. Therefore, an attention-prediction model is constructed to learn the dependency between attention weights and sources.
After revision:  Unlike NMT, NAS is not based on one-to-one transformation. Instead, its attention distribution for the input should be irregular and depend on the content layout of the source documents. To address this matter, we construct an attention-prediction model is constructed to learn the dependency between attention weights and sources.