通过分析作者文风，让故事生成更贴合个人风格。
Whose story is it? Personalizing story generation by inferring author styles
- 构建作者写作特征表，提取隐含写作风格
- 个性化生成故事在风格匹配上胜过基线78%
- 适合教育写作与互动创作场景使用
个性化对交互式写作和教育应用至关重要，但在故事生成领域仍研究不足。本文研究基于作者过往作品生成其个人风格故事的任务。我们构建了包含3.6千篇故事、来自112位作者的Mythos数据集，每位作者平均有16篇故事，涵盖五个不同来源，反映多样化的创作场景。提出两阶段个性化生成流程：首先，推断作者的隐含写作特征并整理为作者写作表（Author Writing Sheet），经人工验证质量较高；其次，通过定制化角色描述与个性化规则模拟作者人格。实验表明，使用作者写作表生成的故事在捕捉作者历史风格方面胜过非个性化基线78%；在与真实作者故事的相似度上达到59%。人工评估支持上述结果，并发现如Reddit故事更易个性化，且创意与语言使用比情节更易模仿。
原文摘要 · Abstract (English)
Personalization is critical for improving user experience in interactive writing and educational applications, yet remains understudied in story generation. We study the task of personalizing story generation, where our goal is to mimic an author's writing style, given other stories written by them. We collect Mythos, a dataset of 3.6k stories from 112 authors, with an average of 16 stories per author, across five distinct sources reflecting diverse story-writing settings. We propose a two-stage pipeline for personalized story generation: first, we infer authors' implicit writing characteristics and organize them into an Author Writing Sheet, which is validated by humans to be of high quality; second, we simulate the author's persona using tailored persona descriptions and personalized story rules. We find that stories personalized using the Author Writing Sheet outperform a non-personalized baseline, achieving a 78% win-rate in capturing authors' past style and 59% in similarity to ground-truth author stories. Human evaluation supports these findings and further highlights trends, such as Reddit stories being easier to personalize, and the Creativity and Language Use aspects of stories being easier to personalize than the Plot.
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