The stylistic properties of text have intrigued computational linguistics researchers in recent
years. Specifically, researchers have investigated the text style transfer task (TST), which …

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 …

Sentiment transfer is one popular example of a text style transfer task, where the goal is to
reverse the sentiment polarity of a text. With a sentiment reversal comes also a reversal in …

Scarcity of parallel data causes formality style transfer models to have scarce success in
preserving content. We show that fine-tuning pre-trained language (GPT-2) and sequence-to …

We take the first step towards multilingual style transfer by creating and releasing
XFORMAL, a benchmark of multiple formal reformulations of informal text in Brazilian …

Text style transfer pursues altering the style of a sentence while remaining its main content
unchanged. Due to the lack of parallel corpora, most recent work focuses on unsupervised …

Formality style transfer is the task of converting informal sentences to grammatically-correct
formal sentences, which can be used to improve performance of many downstream NLP …

Counterfactual generation lies at the core of various machine learning tasks, including
image translation and controllable text generation. This generation process usually requires …

While the field of style transfer (ST) has been growing rapidly, it has been hampered by a
lack of standardized practices for automatic evaluation. In this paper, we evaluate leading …

AI-driven chatbots have become an emerging solution to address psychological distress.
Due to the lack of psychotherapeutic data, researchers use dialogues scraped from online …