For every mini-batch of examples X + Z G , we compute the discrimina-tor loss L(C ; D(X + Z G ; Â)) and apply the negative of this loss to each word of the generated sentence in G s2s .
the discriminator loss value replaces the cross-entropy loss used to train the seq2seq model (similar to a REIN-FORCE (Williams, 1992) reward).