In practise, the pre-trained language model prior p(c) prefers short sentences for compressions.
as one of the drawbacks of VaEs, the KL divergence term in the lower bound pushes every sample drawn Compresser Compression (Combined Pointer Networks) acting to regularise the posterior, but also to restrict the learning of the encoder.