Here, data is embedded into a latent space which is modelled by conditional distributions, and samples from this distributions can be decoded into new artificial data instances.
to shallow models such as Skip-Gram (Mikolov et al., 2013) which also embeds into latent spaces, deep generative models have been shown to capture the implicit semantics and structure of the underlying data more effectively.