Therefore, during translation decoding of NMT, we can drop the coefficient γ and rephrase the source sentence only with the anchor points.
we apply an attention mechanism between current local contextual information and each anchor point v j to get the global context as: where α G tj is the attention score between current local contexts and the global context, computed as: Once the global context c G t is obtained, we feed it to decoder states: where c t encodes the local contextual information and c G t contains the global monolingual information from all source sentences in the training corpus.