分析大模型生成中文网文的叙事同质化问题，揭示其机械套用套路的本质。
Creative Convergence or Imitation? Genre-Specific Homogeneity in LLM-Generated Chinese Literature
- 基于普罗普叙事学扩展出34个适合网络文学的叙事功能
- 发现大模型无法理解叙事意义，仅机械套用固定情节模板
- 构建人工标注语料库，为中文故事生成提供可量化的分析基准
大型语言模型在叙事生成方面表现出色，但常产生结构雷同的故事，频繁重复情节安排与刻板结局。本文结合普罗普叙事学与叙事功能理论，提出新分析框架，用于揭示大模型生成文本背后的叙事逻辑。以中文网络文学为研究对象，将普罗普理论拓展为适用于现代网络叙事的34个叙事功能，并构建人工标注语料库，支持对生成文本结构的分析。实验表明，当前大模型无法正确理解叙事功能含义，而是依赖僵化的生成范式，导致生成内容呈现严重同质化。
原文摘要 · Abstract (English)
Large Language Models (LLMs) have demonstrated remarkable capabilities in narrative generation. However, they often produce structurally homogenized stories, frequently following repetitive arrangements and combinations of plot events along with stereotypical resolutions. In this paper, we propose a novel theoretical framework for analysis by incorporating Proppian narratology and narrative functions. This framework is used to analyze the composition of narrative texts generated by LLMs to uncover their underlying narrative logic. Taking Chinese web literature as our research focus, we extend Propp's narrative theory, defining 34 narrative functions suited to modern web narrative structures. We further construct a human-annotated corpus to support the analysis of narrative structures within LLM-generated text. Experiments reveal that the primary reasons for the singular narrative logic and severe homogenization in generated texts are that current LLMs are unable to correctly comprehend the meanings of narrative functions and instead adhere to rigid narrative generation paradigms.
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