Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research
It addresses the preservation and study of low-resource languages, which are critical for cultural and historical diversity, but is incremental as it reviews existing opportunities and challenges without presenting new experimental results.
This study tackles the problem of data scarcity and technological limitations hindering research on low-resource languages in humanities by evaluating the applications of large language models (LLMs), identifying key challenges like data accessibility and model adaptability, and emphasizing interdisciplinary collaboration and customized models as promising solutions.
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.