发表机构
Human Language Technologies Research Center（人类语言技术研究中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究借鉴模仿理论，构建多层级框架量化分析文学文本在词汇、语义等维度的转化，揭示不同文本对的结构保留与分歧情况，为表征文学中模仿与创造性分歧提供定量方法。
AI 中文摘要
创造力常被界定为新奇事物的产生，但许多文化作品是通过对早期作品的转化而非孤立发明形成的。本文借鉴Gabriel Tarde与James Mark Baldwin的模仿理论，将创造力建模为跨多个文本表征层级的选择性转化。我们引入一个多层级框架，通过定向对齐与控制校准的相似度度量，在词汇、语义、概念、结构及叙事维度上对比文学文本。将该模型应用于历史文献记载的文学关系，结果显示不同文本对在不同表征层级保留源文本结构，同时在其他层级产生差异。这些转化轮廓为量化表征文学作品中模仿的延续及创造性分歧的发生位置提供了方法。
英文摘要
Creativity is often framed as the production of novelty, yet many cultural works emerge through transformation of earlier artifacts and not through isolated invention. Drawing on theories of imitation by Gabriel Tarde and James Mark Baldwin, this paper models creativity as selective transformation across multiple levels of textual representation. We introduce a multi-level framework that compares literary texts across lexical, semantic, conceptual, structural, and narrative dimensions using directional alignment and control calibrated similarity measures. Applying the model to historically documented literary relationships, we show that different pairs preserve source structure at different representational levels while diverging in others. These transformation profiles provide a quantitative method for characterizing how imitation persists and where creative divergence occurs within literary works.
