Text style transfer is an important task in natural language generation, which aims to control
certain attributes in the generated text, such as politeness, emotion, humor, and many …

Automatically disentangling an author's style from the content of their writing is a
longstanding and possibly insurmountable problem in computational linguistics. At the same …

Style representation learning builds content-independent representations of author style in
text. Stylometry, the analysis of style in text, is often performed by expert forensic linguists …

Text Style Transfer (TST) evaluation is, in practice, inconsistent. Therefore, we conduct a
meta-analysis on human and automated TST evaluation and experimentation that …

Humans are naturally endowed with the ability to write in a particular style. They can, for
instance, rephrase a formal letter in an informal way, convey a literal message with the use …

Estimation of semantic similarity is crucial for various natural language processing (NLP)
tasks. In the absence of a general theory of semantic information, many papers rely on …

Text style transfer, an important research direction in natural language processing, aims to
adapt the text to various preferences but often faces challenges with limited resources. In …

Text style transfer aims to change the style (eg, sentiment, politeness) of a sentence while
preserving its content. A common solution is the prototype editing approach, where stylistic …

Research on textual style transfer has observed that the concept of style can vary across
domains. This research examines the encoding of style across the sentiment and formality …

Unsupervised textual style transfer presupposes that style is a coherent and consistent
concept and that style transfer approaches will generalise consistently across different …