Decomposing Textual Information For Style Transfer
Yamshchikov, Ivan P., Shibaev, Viacheslav, Nagaev, Aleksander, Jost, Jürgen, Tikhonov, Alexey
–arXiv.org Artificial Intelligence
However, natural language generation with encoder-decoder based methods but depends is still a challenging task due to a number on the used architecture. Moreover, architectures of factors that include the absence of local information with higher quality of information decomposition continuity and non-smooth disentangled perform better in terms of the style transfer task.
arXiv.org Artificial Intelligence
Sep-26-2019