Papers by Aleksander Nagaev

2 papers
Decomposing Textual Information For Style Transfer (D19-56)

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Challenge: Using a framework of style transfer for texts, we propose several empirical methods to assess information decomposition quality.
Approach: They propose to use latent representations to effectively decompose different aspects of textual information using a framework of style transfer for texts.
Outcome: The proposed methods show that higher quality representations correlate with higher performance in bilingual evaluation understudy (BLEU) between output and human-written reformulations.
Style Transfer for Texts: Retrain, Report Errors, Compare with Rewrites (D19-1)

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Challenge: Currently, standard methods for style transfer have several significant problems.
Approach: They propose to take BLEU between input and human-written reformulations into consideration for benchmarks.
Outcome: The proposed architectures outperform state-of-the-art in style transfer metric on human-written reformulations and take BLEU between input and output into consideration for benchmarks.

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