AI RESEARCH
Lost in Cultural Translation: Do LLMs Struggle with Math Across Cultural Contexts?
arXiv CS.LG
•
ArXi:2503.18018v2 Announce Type: replace-cross We nstrate that large language models' (LLMs) mathematical reasoning is culturally sensitive: testing 14 models from Anthropic, OpenAI, Google, Meta, DeepSeek, Mistral, and Microsoft across six culturally adapted variants of the GSM8K benchmark, we find accuracy drops ranging from 0.3% (Claude 3.5 Sonnet) to 5.9% (LLaMA 3.1-8B) when math problems are embedded in unfamiliar cultural contexts--even when the underlying mathematical logic remains unchanged.