Who Brought Easter Eggs to Eid? Auditing Cultural Translation of Math Word Problems Across Diverse Languages and Regions
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Audit finds cultural translation failures and diversity collapse in LLM-adapted math word problems across 7 languages
Researchers audited how Claude Opus 4, GPT-4.1, and Gemini 2.5 Pro adapt 60 English math word problems into seven languages spanning South Asia and Italy, annotating 6,489 entity transformations. Models agreed on transformation type only 62.5% of the time and on specific substitutions in just 33.5% of cases, meaning model choice substantially shapes the cultural world students encounter. All 21 language-model combinations exhibited 'entropy collapse'—adaptations compressed rather than expanded cultural diversity—and models produced systematic regional misattributions (e.g., Bangladeshi currency for Indian Bengali students) and cross-cultural contamination (e.g., egg hunts framed as Eid activities). The study highlights that surface plausibility masks deeper corpus-level failures invisible in individual translations.