Different from (Cheng et al., 2016;Saha et al., 2016) which adopt the fully shared encoder, we share only partial weights for the encoders, considering that 1) The independent weights are devoted to encode the hidden features about the internal characteristics of each corpus, such as the terminology, style, and sentence structure; 2) The shared weights are concentrated on projecting those hidden features into the shared-latent space.
we share the weights of the last few layers of encoders Enc l and Enc u , which are committed to capture the high-level representations of the input sentences.