AI RESEARCH
Left Behind: Cross-Lingual Transfer as a Bridge for Low-Resource Languages in Large Language Models
arXiv CS.CL
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ArXi:2603.21036v1 Announce Type: new We investigate how large language models perform on low-resource languages by benchmarking eight LLMs across five experimental conditions in English, Kazakh, and Mongolian. Using 50 hand-crafted questions spanning factual, reasoning, technical, and culturally grounded categories, we evaluate 2,000 responses on accuracy, fluency, and completeness.