What is the difference between an autoencoder and an encoder-decoder?
According to section 2.3 of this paper:


  Auto-encoders are special cases of encoder-decoder models in which the input and output are the same.


The same section of the paper describes encoder-decoder as follows:


  Encoder-Decoder models are a family of models which learn to map data-points from an input domain to an output domain via a two-stage network: The encoder, represented by an encoding function z = f(x), compresses the input into a latent-space representation; the decoder, y = g(z), aims to predict the output from the latent space representation.