--- title: "Who cites CulturalBench: A Robust, Diverse — 31 citing papers" description: "31 papers of the Elamur Research library cite «CulturalBench: A Robust, Diverse and Challenging Benchmark for Measuring LMs' Cultural…" canonical: "https://research.elamur.ai/free/en/papers/chiu-2025-culturalbench-robust-diverse-challenging-benchmark/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/chiu-2025-culturalbench-robust-diverse-challenging-benchmark/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [CulturalBench: A Robust, Diverse and Challenging…](https://md.research.elamur.ai/free/en/papers/chiu-2025-culturalbench-robust-diverse-challenging-benchmark/) / cited by # Who cites «CulturalBench: A Robust, Diverse and Challenging Benchmark for Measuring LMs' Cultural Knowledge Through Human-AI Red-Teaming» 31 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «CulturalBench: A Robust, Diverse and Challenging Benchmark for Measuring LMs' Cultural Knowledge Through Human-AI Red-Teaming»](https://md.research.elamur.ai/free/en/papers/chiu-2025-culturalbench-robust-diverse-challenging-benchmark/) 1. **[Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.*2026 · 68 citations* 2. **[A Parallel Cross-Lingual Benchmark for Multimodal Idiomaticity Understanding](https://md.research.elamur.ai/free/en/papers/selamet-2026-parallel-cross-lingual-benchmark-multimodal/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Dilara Torunoğlu-Selamet, Doğukan Arslan, Rodrigo Wilkens, et al.*2026 · 8 citations* 3. **[Localized Cultural Knowledge is Conserved and Controllable in Large Language Models](https://md.research.elamur.ai/free/en/papers/veselovsky-2026-localized-cultural-knowledge-is-conserved/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Veniamin Veselovsky, Berke Argın, Benedikt Stroebl, et al.*2026 · 7 citations* 4. **[BLEnD-Vis: Benchmarking Multimodal Cultural Understanding in Vision Language Models](https://md.research.elamur.ai/free/en/papers/tan-2026-blend-vis-benchmarking-multimodal-cultural/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bryan Chen Zhengyu Tan, Weihua Zheng, Zhengyuan Liu, et al.*2026 · 2 citations* 5. **[Deciphering Cultural Representations in Large Language Models via Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/zou-2026-deciphering-cultural-representations-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenye Zou, Difan Jiao, Lijie Hu*2026 · 1 citation* 6. **[No Shortcuts to Culture: Indonesian Multi-hop Question Answering for Complex Cultural Understanding](https://md.research.elamur.ai/free/en/papers/permadi-2026-no-shortcuts-culture-indonesian-multi/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vynska Amalia Permadi, Xingwei Tan, Nafise Sadat Moosavi, et al.*2026 · 1 citation* 7. **[x1: Learning to Think Adaptively Across Languages and Cultures](https://md.research.elamur.ai/free/en/papers/ye-2026-x1-learning-think-adaptively-across/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangfan Ye, Xiaocheng Feng, Xiachong Feng, et al.*2026 · 1 citation* 8. **[CultranAI at PalmX 2025: Data Augmentation for Cultural Knowledge Representation](https://md.research.elamur.ai/free/en/papers/bhatti-2025-cultranai-palmx-2025-data-augmentation/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Hunzalah Hassan Bhatti, Youssef Ahmed, Md Arid Hasan, et al.*2025 · 1 citation* 9. **[Common to Whom? Regional Cultural Commonsense and LLM Bias in India](https://md.research.elamur.ai/free/en/papers/madhusudan-2026-common-whom-regional-cultural-commonsense/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sangmitra Madhusudan, Trush Shashank More, Steph Buongiorno, et al.*2026* 10. **[Distributional Alignment for Large Language Models under Domain Shift](https://md.research.elamur.ai/free/en/papers/pham-2026-distributional-alignment-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Viet Thanh Pham, Lizhen Qu, Zhuang Li, et al.*2026* 11. [**Figurative and Cultural Knowledge in LLMs: Investigating Cross-Domain Transfer through Fine-Tuning arXiv:2608.18361**Mena Attia, Mona Diab, Thamar Solorio*2026*](https://md.research.elamur.ai/free/en/papers/attia-2026-figurative-cultural-knowledge-llms-investigating/) 12. [**SDUs DAISY: A Benchmark for Danish Culture arXiv:2601.19930**Jacob Nielsen, Stine L. Beltoft, Peter Schneider-Kamp, et al.*2026*](https://md.research.elamur.ai/free/en/papers/nielsen-2026-sdus-daisy-benchmark-danish-culture/) 13. **[UNSC-Bench: Evaluating LLM Diplomatic Role-Playing Through UN Security Council Vote Prediction](https://md.research.elamur.ai/free/en/papers/nangia-2026-unsc-bench-evaluating-llm-diplomatic/) [Workshop on Multilingual Multicultural Evaluation](https://md.research.elamur.ai/free/en/venues/mme/)**Ayush Nangia, Aman Gokrani, Ruggero Marino Lazzaroni*2026* 18 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/chiu-2025-culturalbench-robust-diverse-challenging-benchmark/) — CulturalBench: A Robust, Diverse and Challenging Benchmark for Measuring LMs' Cultural Knowledge Through Human-AI Red-Teaming