Papers with SEA cultural

    1 papers
    SEA-SafeguardBench: Culturally Grounded Safety Benchmark for Southeast Asian Languages (2026.findings-acl)

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    Challenge: Existing multilingual safety benchmarks rely on machine-translated English data, which fails to capture nuances in low-resource languages.
    Approach: They propose to use a human-verified safety benchmark for Southeast Asian languages to validate their safety and cultural diversity.
    Outcome: The proposed model outperforms existing models in general, in-the-wild, and content generation across eight languages and 21,640 samples across three subsets: general, and in- the-wild.

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