Benchmark Almanac

CulturalRiddles

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Models solve original riddles written by people from 62 cultures in 51 languages. Solving them needs cultural knowledge plus abductive and compositional reasoning.

It had 41 Hugging Face paper upvotes and 12 GitHub stars.

In the authors’ words

As LLMs expand their language coverage, evaluating how well they understand and represent diverse cultures becomes increasingly important. However, many benchmarks remain English-centric, with limited cultural coverage and a focus on factual knowledge over its application in real-world cultural contexts. We propose CulturalRiddles, a benchmark of original, culturally grounded riddles created entirely by humans through a participatory community effort, spanning 62 cultures (45 countries, 51 languages). These riddles are deeply rooted in their respective cultures and require abductive and compositional reasoning, alongside detailed factual and social knowledge, language skills, and an understanding of culturally specific associations. We benchmark 28 LLM configurations using both automatic and large-scale human evaluation. Even frontier models achieve at most 22% accuracy in some communities. We publicly release all artifacts alongside an open contribution process to expand the benchmark's linguistic and cultural coverage.

Abstract of CulturalRiddles: A Multicultural Benchmark of Riddles (arXiv:2610.29968, CC0)
Made by Cohere Labs Community Released Oct 2026 Reasoning in many languages All tasks public
Level
Everyday Most adults, without training
Scored
Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
Answers
Short answer A number, word or short string matched to a key.

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No lab, leaderboard or Epoch AI run has reported a score for CulturalRiddles yet.

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We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark.

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