Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research
Summary
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.
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# Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research Source: https://arxiv.org/abs/2412.04497 Authors:Tianyang Zhong (https://arxiv.org/search/cs?searchtype=author&query=Zhong,+T),Zhenyuan Yang (https://arxiv.org/search/cs?searchtype=author&query=Yang,+Z),Zhengliang Liu (https://arxiv.org/search/cs?searchtype=author&query=Liu,+Z),Ruidong Zhang (https://arxiv.org/search/cs?searchtype=author&query=Zhang,+R),Weihang You (https://arxiv.org/search/cs?searchtype=author&query=You,+W),Yiheng Liu (https://arxiv.org/search/cs?searchtype=author&query=Liu,+Y),Haiyang Sun (https://arxiv.org/search/cs?searchtype=author&query=Sun,+H),Yi Pan (https://arxiv.org/search/cs?searchtype=author&query=Pan,+Y),Yiwei Li (https://arxiv.org/search/cs?searchtype=author&query=Li,+Y),Yifan Zhou (https://arxiv.org/search/cs?searchtype=author&query=Zhou,+Y),Hanqi Jiang (https://arxiv.org/search/cs?searchtype=author&query=Jiang,+H),Junhao Chen (https://arxiv.org/search/cs?searchtype=author&query=Chen,+J),Xiang Li (https://arxiv.org/search/cs?searchtype=author&query=Li,+X),Tianming Liu (https://arxiv.org/search/cs?searchtype=author&query=Liu,+T) View PDF (https://arxiv.org/pdf/2412.04497) > Abstract:Low\-resource languages serve as invaluable repositories of human history, embodying cultural evolution and intellectual diversity\. Despite their significance, these languages face critical challenges, including data scarcity and technological limitations, which hinder their comprehensive study and preservation\. Recent advancements in large language models \(LLMs\) offer transformative opportunities for addressing these challenges, enabling innovative methodologies in linguistic, historical, and cultural research\. This study systematically evaluates the applications of LLMs in low\-resource language research, encompassing linguistic variation, historical documentation, cultural expressions, and literary analysis\. By analyzing technical frameworks, current methodologies, and ethical considerations, this paper identifies key challenges such as data accessibility, model adaptability, and cultural sensitivity\. Given the cultural, historical, and linguistic richness inherent in low\-resource languages, this work emphasizes interdisciplinary collaboration and the development of customized models as promising avenues for advancing research in this domain\. By underscoring the potential of integrating artificial intelligence with the humanities to preserve and study humanity's linguistic and cultural heritage, this study fosters global efforts towards safeguarding intellectual diversity\. ## Submission history From: Zhenyuan Yang \[view email (https://arxiv.org/show-email/d325eec7/2412.04497)\] **[\[v1\]](https://arxiv.org/abs/2412.04497v1)**Sat, 30 Nov 2024 00:10:56 UTC \(2,909 KB\) **[\[v2\]](https://arxiv.org/abs/2412.04497v2)**Mon, 9 Dec 2024 03:00:42 UTC \(2,909 KB\) **[\[v3\]](https://arxiv.org/abs/2412.04497v3)**Tue, 2 Sep 2025 08:33:39 UTC \(173 KB\) **[\[v4\]](https://arxiv.org/abs/2412.04497v4)**Mon, 5 Jan 2026 05:58:43 UTC \(158 KB\) **\[v5\]**Fri, 17 Apr 2026 14:43:11 UTC \(158 KB\)
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