Decomposing Textual Information For Style Transfer
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 13 Oct 2026). First posted on arXiv 26 Sep 2019.
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Citing papers per year: 2021: 2; 2022: 1.
3 papers.
- 2021A Novel Estimator of Mutual Information for Learning to Disentangle Textual Representationscited by 37
- 2022T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representationcited by 6
- 2021From Theories on Styles to their Transfer in Text: Bridging the Gap with a Hierarchical Surveycited by 5
- 2022T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation3 Dec 2022
- 2021From Theories on Styles to their Transfer in Text: Bridging the Gap with a Hierarchical Survey29 Oct 2021
- 2021A Novel Estimator of Mutual Information for Learning to Disentangle Textual Representations6 May 2021