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AI predicts Tang Dynasty poets' origins from linguistic fingerprints

Researchers have developed computational models capable of predicting the geographic origins of Tang Dynasty poets based on linguistic patterns in their work. By analyzing the Complete Tang Poems and linking poets to their administrative regions, the models achieved 0.69 accuracy in distinguishing between southern and northern poets, and performed above chance for finer regional distinctions. The study also revealed a linguistic distance decay effect between regions, with the north-south language signal strengthening in the Late Tang period, and found that a classical Chinese transformer model (GuwenBERT) did not outperform simpler TF-IDF methods for this task. AI

IMPACT Demonstrates AI's potential for literary analysis and historical hypothesis generation.

RANK_REASON The cluster contains an academic paper detailing a computational analysis and model application.

Read on arXiv cs.CL →

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AI predicts Tang Dynasty poets' origins from linguistic fingerprints

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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Chi-Sheng Chen, Hung-Yun Liu ·

    Predicting Poets' Origins from Verse: A Computational Analysis of Regional Linguistic Fingerprints in the Complete Tang Poems

    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 …

  2. arXiv cs.CL TIER_1 English(EN) · Hung-Yun Liu ·

    Predicting Poets' Origins from Verse: A Computational Analysis of Regional Linguistic Fingerprints in the Complete Tang Poems

    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…