Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation (2025 · 182 citations)
Multilingual LLMs are often evaluated on machine-translated copies of English MMLU. This adds translation artifacts and keeps a US- and Europe-centred knowledge bias that may not matter to speakers of other languages. The authors measure this bias and build an alternative. Around 200 annotators, both paid…
BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models (2023 · 33 citations)
Most large-scale LLM benchmarks, such as HELM and BIG-bench, focus on English. Southeast Asian (SEA) languages get little systematic evaluation. BHASA addresses this gap with an evaluation suite in three parts:
SEA-LION: Southeast Asian Languages in One Network (2025 · 29 citations)
Most open LLMs are designed around English and perform poorly on Southeast Asian languages. Lower-resource ones such as Burmese, Lao, Khmer and Filipino are hit hardest, and even regional models like SeaLLMs and Sailor fall short on Thai and Tamil. The AI Singapore team responds with SEA-LION, two instruction-tuned…

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Updated 30 October 2026