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QuanLing framework quantifies language distance in Western Romance languages

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Researchers have extended the QuanLing framework, which uses pretrained language models to quantify language distance, to Western Romance languages. This framework combines sentence embedding distances, tokenization fragmentation rates, and masked language model probabilities. The study found that Portuguese and Spanish are the closest among French, Portuguese, Spanish, and Italian, while French and Italian are the most distant. The results suggest that QuanLing is generalizable across different language branches. AI

IMPACT Provides a new quantitative method for analyzing linguistic relationships using AI models.

RANK_REASON Academic paper detailing a new methodology for language distance quantification. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

QuanLing framework quantifies language distance in Western Romance languages

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Academic paper detailing a new methodology for language distance quantification. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Yiping Bai ·

    QuanLing: Cross-Branch Validation of Language Distance Quantification on Western Romance

    arXiv:2610.08851v1 Announce Type: new Abstract: Quantifying language distance among closely related languages remains a core challenge in quantitative linguistics. Our previous work [1] introduced QuanLing (Quantitative Linguistics via Pretrained Language Models), a quantitative …

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