English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Unsupervised text style transfer task aims to rewrite a text into targetstyle while preserving its main content. Traditional methods rely on the use ofa fixed-sized vector to regulate text style, which is difficult to accuratelyconvey the style strength for each individual token. In fact, each token of atext contains different style intensity and makes different contribution to theoverall style. Our proposed method addresses this issue by assigning individualstyle vector to each token in a text, allowing for fine-grained control andmanipulation of the style strength. Additionally, an adversarial trainingframework integrated with teacher-student learning is introduced to enhancetraining stability and reduce the complexity of high-dimensional optimization.The results of our experiments demonstrate the efficacy of our method in termsof clearly improved style transfer accuracy and content preservation in bothtwo-style transfer and multi-style transfer settings.

MSSRNet: Manipulating Sequential Style Representation for Unsupervised Text Style Transfer