arXiv:2604.26656cs.CL2026-04

差分隐私重写会改变文本风格,让语言变得中性无感。

Differentially-Private Text Rewriting reshapes Linguistic Style

  • 用语言模型进行句子级重写实现文本差分隐私
  • 隐私保护导致互动标记和复杂句式大幅减少
  • 适合关注隐私与语言风格平衡的研究者

差分隐私在文本领域的应用已从零散的词级替换发展到利用语言模型生成能力的连续句级重写。尽管这种文本私有化方法在保障隐私与语法连贯性之间取得良好平衡,但其对文本语域特征的影响仍不清楚。通过多维度风格分析发现,隐私约束下的重写不仅带来词汇变化,更导致文本交际特征的系统性变异:交互标记、语境指涉和复杂从属结构显著削弱。比较自回归重写与双向替换在不同隐私预算下的表现,两者均使文本趋向非参与、非说服性的语域。这种无语域的净化虽保留了语义内容,却结构化地同质化了人类写作中的细微风格标记。

原文摘要 · Abstract (English)

Differential Privacy (DP) for text matured from disjointed word-level substitutions to contiguous sentence-level rewriting by leveraging the generative capacity of language models. While this form of text privatization is best suited for balancing formal privacy guarantees with grammatical coherence, its impact on the register identity of text remains largely unexplored. By conducting a multidimensional stylistic profiling of differentially-private rewriting, we demonstrate that the cost of privacy extends far beyond lexical variation. Specifically, we find that rewriting under privacy constraints induces a systematic functional mutation of the text's communicative signature. This shift is characterized by the severe attrition of interactive markers, contextual references, and complex subordination. By comparing autoregressive paraphrasing against bidirectional substitution across a spectrum of privacy budgets, we observe that both architectures force convergence toward a non-involved and non-persuasive register. This register-blind sanitization effectively preserves semantic content but structurally homogenizes the nuanced stylistic markers that define human-authored discourse.

差分隐私风格迁移文本生成

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