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Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages

Naous, Tarek et al.
arXiv (All) · Papers
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computation-and-language
As Large Language Models (LLMs) develop stronger multilingual capabilities, their sensitivity to culturally diverse entities becomes increasingly important. Prior work by Naous et al. (2024) has shown that LLMs often favor Western-associated entities in Arabic. Due to the lack of entity-centric mult
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