研究人员开发了计算模型，能够根据诗人作品中的语言模式预测其籍贯。通过分析《全唐诗》并将诗人与其行政区域联系起来，模型在区分南北诗人方面达到了0.69的准确率，并在更精细的区域区分方面表现优于随机猜测。研究还揭示了区域间的语言距离衰减效应，南北语言信号在晚唐时期有所增强，并发现古文 transformer 模型（GuwenBERT）在此任务上的表现并不优于更简单的 TF-IDF 方法。 AI
影响 展示了AI在文学分析和历史假设生成方面的潜力。
排序理由 该集群包含一篇详细介绍计算分析和模型应用的学术论文。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2606.24093v1 Announce Type: cross Abstract: We ask whether the geographic origin of Tang-dynasty poets leaves a detectable linguistic trace in their work. Aggregating every poem attributed to each author in the Complete Tang Poems (Quan Tang Shi) and linking poets to their …
We ask whether the geographic origin of Tang-dynasty poets leaves a detectable linguistic trace in their work. Aggregating every poem attributed to each author in the Complete Tang Poems (Quan Tang Shi) and linking poets to their administrative circuit of origin via the China Bio…