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

arXiv: https://arxiv.org/abs/2503.15003 · HTML: https://mlsanity.com/paper/2503.15003/

## 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 (most cited first, 20 of 20)

- [Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study](https://mlsanity.com/paper/2303.17466/) (2023)
- [Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation](https://mlsanity.com/paper/2412.03304/) (2024)
- [BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages](https://mlsanity.com/paper/2406.09948/) (2024)
- [Towards Measuring and Modeling "Culture" in LLMs: A Survey](https://mlsanity.com/paper/2403.15412/) (2024)
- [Investigating Cultural Alignment of Large Language Models](https://mlsanity.com/paper/2402.13231/) (2024)
- [Multilingual and Multi-Aspect Hate Speech Analysis](https://mlsanity.com/paper/1908.11049/) (2019)
- [ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic](https://mlsanity.com/paper/2402.12840/) (2024)
- [AceGPT, Localizing Large Language Models in Arabic](https://mlsanity.com/paper/2309.12053/) (2023)
- [Fanar: An Arabic-Centric Multimodal Generative AI Platform](https://mlsanity.com/paper/2501.13944/) (2025)
- [Unintended Impacts of LLM Alignment on Global Representation](https://mlsanity.com/paper/2402.15018/) (2024)
- [AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs](https://mlsanity.com/paper/2409.11404/) (2024)
- [Exploring Cross-Cultural Differences in English Hate Speech Annotations: From Dataset Construction to Analysis](https://mlsanity.com/paper/2308.16705/) (2023)
- [Peacock: A Family of Arabic Multimodal Large Language Models and Benchmarks](https://mlsanity.com/paper/2403.01031/) (2024)
- [What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialects](https://mlsanity.com/paper/2402.11968/) (2024)
- [CIDAR: Culturally Relevant Instruction Dataset For Arabic](https://mlsanity.com/paper/2402.03177/) (2024)
- [Towards Responsible Natural Language Annotation for the Varieties of Arabic](https://mlsanity.com/paper/2203.09597/) (2022)
- [Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect](https://mlsanity.com/paper/2409.17912/) (2024)
- [Why AI Is WEIRD and Should Not Be This Way: Towards AI For Everyone, With Everyone, By Everyone](https://mlsanity.com/paper/2410.16315/) (2024)
- [Swan and ArabicMTEB: Dialect-Aware, Arabic-Centric, Cross-Lingual, and Cross-Cultural Embedding Models and Benchmarks](https://mlsanity.com/paper/2411.01192/) (2024)
- [Estimating the Level of Dialectness Predicts Interannotator Agreement in Multi-dialect Arabic Datasets](https://mlsanity.com/paper/2405.11282/) (2024)

## Built on by (most cited first, 6 of 6)

- [The Alignment Veto: How Safety Training Suppresses Cultural Knowledge in LLMs](https://mlsanity.com/paper/2510.13154/) (2025)
- [Mind the Gap in Cultural Alignment: Task-Aware Culture Management for Large Language Models](https://mlsanity.com/paper/2602.22475/) (2026)
- [Many Dialects, Many Languages, One Cultural Lens: Evaluating Multilingual VLMs for Bengali Culture Understanding Across Historically Linked Languages and Regional Dialects](https://mlsanity.com/paper/2603.21165/) (2026)
- [Structuring the Space of Sociotechnical Alignment](https://mlsanity.com/paper/2607.01250/) (2026)
- [Romanized Arabic Across Dialects: Views, Usage Patterns, and Linguistic Variation](https://mlsanity.com/paper/2608.02555/) (2026)
- [Beyond Good Intentions: When Does the Framing of Multilingual and Low-Resource NLP Research Become a Caricature?](https://mlsanity.com/paper/2608.30866/) (2026)

## 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.