--- title: "Who cites CULTURE-GEN: Revealing — 40 citing papers" description: "40 papers of the Elamur Research library cite «CULTURE-GEN: Revealing Global Cultural Perception in Language Models through Natural…" canonical: "https://research.elamur.ai/free/en/papers/li-2024-culture-gen-revealing-global-cultural/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/li-2024-culture-gen-revealing-global-cultural/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [CULTURE-GEN: Revealing Global Cultural Perception…](https://md.research.elamur.ai/free/en/papers/li-2024-culture-gen-revealing-global-cultural/) / cited by # Who cites «CULTURE-GEN: Revealing Global Cultural Perception in Language Models through Natural Language Prompting» 40 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 «CULTURE-GEN: Revealing Global Cultural Perception in Language Models through Natural Language Prompting»](https://md.research.elamur.ai/free/en/papers/li-2024-culture-gen-revealing-global-cultural/) 1. **[Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation](https://md.research.elamur.ai/free/en/papers/singh-2025-global-mmlu-understanding-addressing-cultural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shivalika Singh, Angelika Romanou, Clémentine Fourrier, et al.*2025 · 182 citations* 2. **[Survey of Cultural Awareness in Language Models: Text and Beyond](https://md.research.elamur.ai/free/en/papers/pawar-2025-survey-cultural-awareness-language-models/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Siddhesh Pawar, Junyeong Park, Jiho Jin, et al.*2025 · 106 citations* 3. **[Towards Measuring and Modeling “Culture” in LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/adilazuarda-2024-measuring-modeling-culture-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Muhammad Farid Adilazuarda, Sagnik Mukherjee, Pradhyumna Lavania, et al.*2024 · 102 citations* 4. **[Culture is Not Trivia: Sociocultural Theory for Cultural NLP](https://md.research.elamur.ai/free/en/papers/zhou-2025-culture-is-not-trivia-sociocultural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Naitian Zhou, David Bamman, Isaac L. Bleaman*2025 · 33 citations* 5. **[CaLMQA: Exploring culturally specific long-form question answering across 23 languages](https://md.research.elamur.ai/free/en/papers/arora-2025-calmqa-exploring-culturally-specific-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shane Arora, Marzena Karpinska, Hung-Ting Chen, et al.*2025 · 27 citations* 6. **[Diffusion Models Through a Global Lens: Are They Culturally Inclusive?](https://md.research.elamur.ai/free/en/papers/bayramli-2025-diffusion-models-through-global-lens/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zahra Bayramli, Ayhan Suleymanzade, Na Min An, et al.*2025 · 11 citations* 7. **[Igniting Creative Writing in Small Language Models: LLM-as-a-Judge versus Multi-Agent Refined Rewards](https://md.research.elamur.ai/free/en/papers/wei-2025-igniting-creative-writing-small-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaolong Wei, Bo Lu, Xingyu Zhang, et al.*2025 · 10 citations* 8. **[Multiple LLM Agents Debate for Equitable Cultural Alignment](https://md.research.elamur.ai/free/en/papers/ki-2025-multiple-llm-agents-debate-equitable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dayeon Ki, Rachel Rudinger, Tianyi Zhou, et al.*2025 · 10 citations* 9. **[Beyond Monolithic Culture: Evaluating Understandability of Online Text Across Cultural Dimensions](https://md.research.elamur.ai/free/en/papers/pandey-2026-beyond-monolithic-culture-evaluating-understandability/) [Workshop on Cross-Cultural Considerations in NLP](https://md.research.elamur.ai/free/en/venues/c3nlp/)**Saurabh Kumar Pandey, Harshit Gupta, Sougata Saha, et al.*2026* 10. **[Cultural and Knowledge Biases in LLMs through the Lens of Entity-Aware Machine Translation](https://md.research.elamur.ai/free/en/papers/xu-2026-cultural-knowledge-biases-llms-through/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Lu Xu, Luca Moroni, Roberto Navigli*2026* 11. **[DRInQ: Evaluating Conversational Implicature with Controlled Context Variation](https://md.research.elamur.ai/free/en/papers/arai-2026-drinq-evaluating-conversational-implicature-controlled/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hirona Jacqueline Arai, Xiang Ren*2026* 12. **[InsideOut: Measuring and Mitigating Insider–Outsider Bias in Interview Script Generation](https://md.research.elamur.ai/free/en/papers/wan-2026-insideout-measuring-mitigating-insider-outsider/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Wan, Xingrun Chen, Kai-Wei Chang*2026* 13. **[Mitigating Cultural Bias in LLMs via Multi-Agent Cultural Debate](https://md.research.elamur.ai/free/en/papers/tan-2026-mitigating-cultural-bias-llms-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qian Tan, Lei Jiang, Yuting Zeng, et al.*2026* 27 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/li-2024-culture-gen-revealing-global-cultural/) — CULTURE-GEN: Revealing Global Cultural Perception in Language Models through Natural Language Prompting