Papers
arxiv:2109.03910
A Recipe For Arbitrary Text Style Transfer with Large Language Models
Published on Sep 8, 2021
Authors:
Abstract
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."
Models citing this paper 0
No model linking this paper
Cite arxiv.org/abs/2109.03910 in a model README.md to link it from this page.
Datasets citing this paper 0
No dataset linking this paper
Cite arxiv.org/abs/2109.03910 in a dataset README.md to link it from this page.
Spaces citing this paper 0
No Space linking this paper
Cite arxiv.org/abs/2109.03910 in a Space README.md to link it from this page.