Steering Large Language Models with Register Analysis for Arbitrary Style Transfer

Fuente: arXiv
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Auteurs principaux: Yang, Xinchen, Carpuat, Marine
Format: Preprint
Publié: 2025
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author Yang, Xinchen
Carpuat, Marine
author_facet Yang, Xinchen
Carpuat, Marine
contents Large Language Models (LLMs) have demonstrated strong capabilities in rewriting text across various styles. However, effectively leveraging this ability for example-based arbitrary style transfer, where an input text is rewritten to match the style of a given exemplar, remains an open challenge. A key question is how to describe the style of the exemplar to guide LLMs toward high-quality rewrites. In this work, we propose a prompting method based on register analysis to guide LLMs to perform this task. Empirical evaluations across multiple style transfer tasks show that our prompting approach enhances style transfer strength while preserving meaning more effectively than existing prompting strategies.
format Preprint
id arxiv_https___arxiv_org_abs_2505_00679
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Steering Large Language Models with Register Analysis for Arbitrary Style Transfer
Yang, Xinchen
Carpuat, Marine
Computation and Language
Large Language Models (LLMs) have demonstrated strong capabilities in rewriting text across various styles. However, effectively leveraging this ability for example-based arbitrary style transfer, where an input text is rewritten to match the style of a given exemplar, remains an open challenge. A key question is how to describe the style of the exemplar to guide LLMs toward high-quality rewrites. In this work, we propose a prompting method based on register analysis to guide LLMs to perform this task. Empirical evaluations across multiple style transfer tasks show that our prompting approach enhances style transfer strength while preserving meaning more effectively than existing prompting strategies.
title Steering Large Language Models with Register Analysis for Arbitrary Style Transfer
topic Computation and Language
url https://arxiv.org/abs/2505.00679