Jürgen Jost
2019
Decomposing Textual Information For Style Transfer
Ivan P. Yamshchikov
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Viacheslav Shibaev
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Aleksander Nagaev
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Jürgen Jost
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Alexey Tikhonov
Proceedings of the 3rd Workshop on Neural Generation and Translation
This paper focuses on latent representations that could effectively decompose different aspects of textual information. Using a framework of style transfer for texts, we propose several empirical methods to assess information decomposition quality. We validate these methods with several state-of-the-art textual style transfer methods. Higher quality of information decomposition corresponds to higher performance in terms of bilingual evaluation understudy (BLEU) between output and human-written reformulations.
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