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.

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