Hence, all of the possible replies to X must be stored within the decoder's probability distribution P (Y |X), and during decoding it is hard to disentangle these possible replies.
our model contains a stochastic component z in the decoder P (Y |z, X), and so by sampling different z and then performing ML decoding on P (Y |z, X), we hope to tease apart the replies stored in the probability distribution P (Y |X), without resorting to sampling from the decoder.