Our model leverages a multitasking framework to train both a summarization model on headline-article pairs, and a Denoising Autoencoder (DAE) on a style corpus.
based on the transformer architecture (Vaswani et al., 2017), we use the style-dependent layer normalization and the style-guided encoder-attention to disentangle the language style factors from the text.