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cs.CL2025★ 1 cited
LAG-MMLU: Benchmarking Frontier LLM Understanding in Latvian and Giriama
Naome A. Etori, Kevin Lu, Randu Karisa +1
As large language models (LLMs) rapidly advance, evaluating their performance is critical. LLMs are trained on multilingual data, but their reasoning abilities are mainly evaluated…
cs.CL2024
Towards Safe Multilingual Frontier AI
Artūrs Kanepajs, Vladimir Ivanov, Richard Moulange
Linguistically inclusive LLMs -- which maintain good performance regardless of the language with which they are prompted -- are necessary for the diffusion of AI benefits around th…