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A preprint proposes a 33-feature quantitative linguistic framework that distinguishes professionally edited from self-published books and outperforms existing story-level evaluation metrics.
This paper systematically evaluates the applications of large language models in low-resource language research, analyzing opportunities and challenges across linguistic variation, historical documentation, cultural expressions, and literary analysis. The study emphasizes interdisciplinary collaboration and customized model development to preserve linguistic and cultural heritage while addressing issues of data accessibility, model adaptability, and cultural sensitivity.