Learning Text Styles: A Study on Transfer, Attribution, and Verification

Zhiqiang Hu

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arXiv · 2507.16530

Learning Text Styles: A Study on Transfer, Attribution, and Verification

Zhiqiang Hu

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Abstract

This thesis advances the computational understanding and manipulation of text styles through three interconnected pillars: (1) Text Style Transfer (TST), which alters stylistic properties (e.g., sentiment, formality) while preserving content; (2)Authorship Attribution (AA), identifying the author of a text via stylistic fingerprints; and (3) Authorship Verification (AV), determining whether two texts share the same authorship. We address critical challenges in these areas by leveraging parameter-efficient adaptation of large language models (LLMs), contrastive disentanglement of stylistic features, and instruction-based fine-tuning for explainable verification.

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Zhiqiang Hu. 2025-07-22. Learning Text Styles: A Study on Transfer, Attribution, and Verification. https://arxiv.org/abs/2507.16530

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