Through the encoder, at each step, the previous line L i−1 , current line L i and title T are represented as concatenated forward and backward 5 vectors Following previous work (Kingma and Welling, 2014; Zhao et al., 2017; Yang et al., 2017), we assume that the variational approximate posterior is a multivariate Gaussian N with a diagonal covariance structure q φ (z|x, c) = N (µ, σ 2 I).
µ and σ are the key parameters 6 to be learned, and they are computed by where W q and b q are trainable parameters.