Formally, the FUTURE layer is a recurrent neural network (the first gray layer in Figure 2) , and its state at time step t is computed by where F is the activation function for the FUTURE layer.
we attribute the former case to the lack of untranslated future modeling, and the latter one to the overloaded use of the decoder state where the language modeling of the decoder leads to the fluent but wrong predictions.