Contextualizing Variation in Text Style Transfer Datasets
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Abstract (arXiv)
Text style transfer involves rewriting the content of a source sentence in a target style. Despite there being a number of style tasks with available data, there has been limited systematic discussion of how text style datasets relate to each other. This understanding, however, is likely to have implications for selecting multiple data sources for model training. While it is prudent to consider inherent stylistic properties when determining these relationships, we also must consider how a style is realized in a particular dataset. In this paper, we conduct several empirical analyses of existing text style datasets. Based on our results, we propose a categorization of stylistic and dataset properties to consider when utilizing or comparing text style datasets.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 26 of its 66 references that are in the map. First posted on arXiv 17 Aug 2021.
Builds on
26 of 66 references.
References · 26
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14 more
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