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CulturalRiddles:覆盖 62 种文化的谜语基准测试

CulturalRiddles: A Multicultural Benchmark of Riddles

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研究者提出 CulturalRiddles,一个完全由人类通过社区协作创作的原创文化谜语基准,覆盖 62 种文化(45 个国家、51 种语言)。该基准要求模型具备溯因与组合推理、事实与社会知识及文化特定联想理解,团队用自动与大规模人工评估测试了 28 种 LLM 配置,前沿模型在部分文化社区中准确率最高仅 22%。所有成果已公开,并开放贡献流程以扩展语言与文化覆盖。

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Authors:My Chiffon Nguyen, Tianyi Hu, Vinod Anbalagan, Henry Gagnier, Pouya Sadeghi, Farah Abdou, Tidor-Vlad Pricope, Diego MMS Oliveira, Jocelyn K D'Arcy, Madeline Smith, Oluwaseun A Ajayi, Yusser Al Ghussin, Zena Al-Khalili, Micol Altomare, Shayan Amir, Ahanaf Aziz, Bryan Chen, Ruchira Dhar, Abdellah El Mekki, Rawan Mohammed Elframawy, Akhil Eppa, Silvia Fernandez, Alex Gimei, Arya Hariharan, Christian Hoang, RamMohanRao Kadiyala, Diana Kozachek, Peerat Limkonchotiwat, Ankita Maity, Di Mo, Ayush Munot, Aylin Naebzadeh, Anastasiia Nikitina, Dina Pisarevskaya, Divas Poudel, Jebish Purbey, Md Rabius Sany Apu, Ahmad Mufli Ramadhan, Ralitza Nikolova Rizova, Diogo M. Serrano-Miranda, Vivek Gopalkrishna Silimkhan, Luis Fernando Solis Navarro, Kaiser Sun, Arya Suneesh, Manaswitha Sunkara, Tejaswi Sunkara, Jonathan E Swindell, Hanna Yukhymenko, Jingyi Zheng, Esther Adenuga, Ilia Afanasev, Wafa Aissa, Lisa Alazraki, Lauren C Altomare, Priscilla Amondi Amuok, Emile Anand, Gabriel Assis, José Matías Avalos, Silvia Lorena Avila, Zakaria Baannou, Niyati Bafna, Yash Bagla, Sarah Bahrami, Bontu F Balcha, Vanya Bannihatti Kumar, Irene Baucells, Abdumutalib Begmuratov, Naman Bhatia, Souvik Bhattacharyya, Isabel Blanco Ferreiro, Felipe Bochini, Sayuru Bopitiya, Angana Borah, Tulika Bose, Olena Bugaiova, Juliana Carvalho, Nancy F Chen, Stephy Chen, Rochelle Choenni, Jayanth Krishna Chundru, Leandro A Cossio, Nebojša Damnjanović, Ona de Gibert, Marco De Santis, Pedro Delgado, Kaustubh Dholé, Adnan El Assadi, Wesam El-Sayed, Nadine M Elframawy, Oumayma Essarhi, Naome A Etori, Reuben Chagas Fernandes, Saanidhi Pravin Gade, Javier García Gilabert, Álvaro González-Escapa, Bin Hu, Kaiyu Huang, Abderrahmane Issam, Danka Jokić, Ulugbek Khalilov

et al. (58 additional authors not shown)

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Abstract: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.
Comments: 37 pages. Dataset: this https URL Code: this https URL
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2610.29968 [cs.CL]
  (or arXiv:2610.29968v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2610.29968

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Pouya Sadeghi [view email]
[v1] Wed, 21 Oct 2026 16:20:30 UTC (3,177 KB)

来源:HuggingFace Daily Papers · arxiv.org