mlsanityData to 7 Oct 2026

Why are all LLMs Obsessed with Japanese Culture? On the Hidden Cultural and Regional Biases of LLMs

arXiv 2604.21751 ↗First posted 23 Apr 2026cs.CL cs.AI cs.CYcited by 1

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Abstract (arXiv)

LLMs have limitations when it comes to cultural coverage and competence, and in some cases, show specific cultural biases. Although prior studies have examined the cultural capabilities of LLMs, none have specifically investigated their regional preferences in generic culture-related questions. In this work, we propose a new dataset based on a comprehensive taxonomy of Culture-Related Open Questions (CROQ), with questions available in 24 languages. We evaluate LLMs by prompting them to answer questions from CROQ and provide a sample location. The results show that, contrary to previous cultural bias work, LLMs show a clear tendency towards countries such as Japan in their answers. Moreover, our results show that when prompting in languages such as English or other high-resource ones, LLMs tend to provide more diverse outputs. Low-resource languages, on the other hand, show more inclinations towards answering questions highlighting countries for which the input language is an official language. Finally, we also investigate at which point of LLM training this cultural bias emerges, with our results suggesting that the first clear signs appear after supervised fine-tuning, and not during pre-training. Dataset available at https://huggingface.co/datasets/HiTZ/CROQ

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 20 references that are in the map. First posted on arXiv 23 Apr 2026.

Builds on

14 of 20 references.

References · 14

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2024Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluationcited by 181
  3. 2024BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languagescited by 171
  4. 2024Towards Measuring and Modeling "Culture" in LLMs: A Surveycited by 166
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  8. 2023Exploring Cross-Cultural Differences in English Hate Speech Annotations: From Dataset Construction to Analysiscited by 44
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  10. 2024NativQA: Multilingual Culturally-Aligned Natural Query for LLMscited by 30
  11. 2025OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokenscited by 27
  12. 2025LLMs and Cultural Values: the Impact of Prompt Language and Explicit Cultural Framingcited by 17
2 more
  1. 2025CulFiT: A Fine-grained Cultural-aware LLM Training Paradigm via Multilingual Critique Data Synthesiscited by 14
  2. 2025MAKIEval: A Multilingual Automatic WiKidata-based Framework for Cultural Awareness Evaluation for LLMscited by 13

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