In this paper, we leverage large language models (LMs) to perform zero-shot text style transfer. We present a prompting method that we call augmented zero-shot learning, which frames style transfer as a sentence rewriting task and requires only a natural language instruction, without model fine-tuning or exemplars in the target style. Augmented zero-shot learning is simple and demonstrates promising results not just on standard style transfer tasks such as sentiment, but also on arbitrary transformations such as "make this melodramatic" or "insert a metaphor."
@article{arxiv.2109.03910,
title = {A Recipe For Arbitrary Text Style Transfer with Large Language Models},
author = {Emily Reif and Daphne Ippolito and Ann Yuan and Andy Coenen and Chris Callison-Burch and Jason Wei},
journal= {arXiv preprint arXiv:2109.03910},
year = {2022}
}