(2018) shows the attention mechanism is so powerful that removing other connections between the encoder and decoder has little effect on BLEU scores in machine translation.
a VED with deterministic attention might learn reconstruction mostly from attention, whereas the posterior of the latent space can fit to its prior in order to minimize the KL term.