mlsanityData to 14 Oct 2026

LLM Alignment for the Arabs: A Homogenous Culture or Diverse Ones?

arXiv 2503.15003 ↗First posted 19 Mar 2025cs.CLcited by 6

Not on the map. Why?

Abstract (arXiv)

Large language models (LLMs) have the potential of being useful tools that can automate tasks and assist humans. However, these models are more fluent in English and more aligned with Western cultures, norms, and values. Arabic-specific LLMs are being developed to better capture the nuances of the Arabic language, as well as the views of the Arabs. Yet, Arabs are sometimes assumed to share the same culture. In this position paper, I discuss the limitations of this assumption and provide preliminary thoughts for how to build systems that can better represent the cultural diversity within the Arab world. The invalidity of the cultural homogeneity assumption might seem obvious, yet, it is widely adopted in developing multilingual and Arabic-specific LLMs. I hope that this paper will encourage the NLP community to be considerate of the cultural diversity within various communities speaking the same language.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 20 of its 45 references that are in the map. First posted on arXiv 19 Mar 2025.

Builds on

20 of 45 references.

References · 20

  1. 2023Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Studycited by 206
  2. 2024Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluationcited by 191
  3. 2024BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languagescited by 173
  4. 2024Towards Measuring and Modeling "Culture" in LLMs: A Surveycited by 167
  5. 2024Investigating Cultural Alignment of Large Language Modelscited by 143
  6. 2019Multilingual and Multi-Aspect Hate Speech Analysiscited by 133
  7. 2024ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabiccited by 88
  8. 2023AceGPT, Localizing Large Language Models in Arabiccited by 75
  9. 2025Fanar: An Arabic-Centric Multimodal Generative AI Platformcited by 67
  10. 2024Unintended Impacts of LLM Alignment on Global Representationcited by 66
  11. 2024AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMscited by 46
  12. 2023Exploring Cross-Cultural Differences in English Hate Speech Annotations: From Dataset Construction to Analysiscited by 45
8 more
  1. 2024Peacock: A Family of Arabic Multimodal Large Language Models and Benchmarkscited by 32
  2. 2024What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialectscited by 21
  3. 2024CIDAR: Culturally Relevant Instruction Dataset For Arabiccited by 17
  4. 2022Towards Responsible Natural Language Annotation for the Varieties of Arabiccited by 14
  5. 2024Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialectcited by 13
  6. 2024Why AI Is WEIRD and Should Not Be This Way: Towards AI For Everyone, With Everyone, By Everyonecited by 10
  7. 2024Swan and ArabicMTEB: Dialect-Aware, Arabic-Centric, Cross-Lingual, and Cross-Cultural Embedding Models and Benchmarkscited by 10
  8. 2024Estimating the Level of Dialectness Predicts Interannotator Agreement in Multi-dialect Arabic Datasetscited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 5.

6 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025NileChat: Towards Linguistically Diverse and Culturally Aware LLMs for Local Communities
  2. 2023CDEval: A Benchmark for Measuring the Cultural Dimensions of Large Language Models
  3. 2026Cultural Benchmarking of LLMs in Standard and Dialectal Arabic Dialogues
  4. 2026Understanding Cultural Alignment in Multilingual LLMs via Natural Debate Statements ↗
  5. 2025Commonsense Reasoning in Arab Culture
  6. 2024Alignment at Pre-training! Towards Native Alignment for Arabic LLMs
  7. 2025Cross-Cultural Transfer of Commonsense Reasoning in LLMs: Evidence from the Arab World
  8. 2026AlignCultura: Towards Culturally Aligned Large Language Models?