Learning Text Styles: A Study on Transfer, Attribution, and Verification
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.引用本文复制引用
Zhiqiang Hu.Learning Text Styles: A Study on Transfer, Attribution, and Verification[EB/OL].(2025-07-22)[2026-04-03].https://arxiv.org/abs/2507.16530.学科分类
语言学
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