# Nile-Chat: Egyptian Language Models for Arabic and Latin Scripts

arXiv: https://arxiv.org/abs/2507.04569 · HTML: https://mlsanity.com/paper/2507.04569/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 31 of its 57 references that are in the map.
- First posted on arXiv 6 Jul 2025.

## Builds on (most cited first, 30 of 31)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena](https://mlsanity.com/paper/2306.05685/) (2023)
- [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://mlsanity.com/paper/2305.18290/) (2023)
- [Measuring Massive Multitask Language Understanding](https://mlsanity.com/paper/2009.03300/) (2020)
- [HellaSwag: Can a Machine Really Finish Your Sentence?](https://mlsanity.com/paper/1905.07830/) (2019)
- [PIQA: Reasoning about Physical Commonsense in Natural Language](https://mlsanity.com/paper/1911.11641/) (2019)
- [Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering](https://mlsanity.com/paper/1809.02789/) (2018)
- [No Language Left Behind: Scaling Human-Centered Machine Translation](https://mlsanity.com/paper/2207.04672/) (2022)
- [LIMA: Less Is More for Alignment](https://mlsanity.com/paper/2305.11206/) (2023)
- [Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators](https://mlsanity.com/paper/2404.04475/) (2024)
- [RACE: Large-scale ReAding Comprehension Dataset From Examinations](https://mlsanity.com/paper/1704.04683/) (2017)
- [Enhancing Chat Language Models by Scaling High-quality Instructional Conversations](https://mlsanity.com/paper/2305.14233/) (2023)
- [WizardCoder: Empowering Code Large Language Models with Evol-Instruct](https://mlsanity.com/paper/2306.08568/) (2023)
- [OpenAssistant Conversations -- Democratizing Large Language Model Alignment](https://mlsanity.com/paper/2304.07327/) (2023)
- [WildChat: 1M ChatGPT Interaction Logs in the Wild](https://mlsanity.com/paper/2405.01470/) (2024)
- [AraBERT: Transformer-based Model for Arabic Language Understanding](https://mlsanity.com/paper/2003.00104/) (2020)
- [The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://mlsanity.com/paper/2308.16884/) (2023)
- [FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language](https://mlsanity.com/paper/2506.20920/) (2025)
- [The Art of Saying No: Contextual Noncompliance in Language Models](https://mlsanity.com/paper/2407.12043/) (2024)
- [ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic](https://mlsanity.com/paper/2402.12840/) (2024)
- [Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning](https://mlsanity.com/paper/2402.04833/) (2024)
- [AceGPT, Localizing Large Language Models in Arabic](https://mlsanity.com/paper/2309.12053/) (2023)
- [Table-GPT: Table-tuned GPT for Diverse Table Tasks](https://mlsanity.com/paper/2310.09263/) (2023)
- [Theory on Mixture-of-Experts in Continual Learning](https://mlsanity.com/paper/2406.16437/) (2024)
- [AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs](https://mlsanity.com/paper/2409.11404/) (2024)
- [WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild](https://mlsanity.com/paper/2409.03753/) (2024)
- [Arabizi Detection and Conversion to Arabic](https://mlsanity.com/paper/1306.6755/) (2013)
- [Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect](https://mlsanity.com/paper/2409.17912/) (2024)
- [AL-QASIDA: Analyzing LLM Quality and Accuracy Systematically in Dialectal Arabic](https://mlsanity.com/paper/2412.04193/) (2024)
- [EgyBERT: A Large Language Model Pretrained on Egyptian Dialect Corpora](https://mlsanity.com/paper/2408.03524/) (2024)

## Built on by (most cited first, 7 of 7)

- [GreekMMLU: A Native-Sourced Multitask Benchmark for Evaluating Language Models in Greek](https://mlsanity.com/paper/2602.05150/) (2026)
- [From FusHa to Folk: Exploring Cross-Lingual Transfer in Arabic Language Models](https://mlsanity.com/paper/2602.09826/) (2026)
- [Linear Semantic Segmentation for Low-Resource Spoken Dialects](https://mlsanity.com/paper/2605.06276/) (2026)
- [Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Translation](https://mlsanity.com/paper/2511.17290/) (2025)
- [MixtureKit: A General Framework for Composing, Training, and Visualizing Mixture-of-Experts Models](https://mlsanity.com/paper/2512.12121/) (2025)
- [The Hrunting of AI: Where and How to Improve English Dialectal Fairness](https://mlsanity.com/paper/2603.15187/) (2026)
- [Some Dialects Are More Equal Than Others: Non-Prestigious Arabic Dialectal Bias in LLMs](https://mlsanity.com/paper/2609.23955/) (2026)

## Abstract (arXiv)

We introduce Nile-Chat-4B, 3x4B-A6B, and 12B, a collection of LLMs for Egyptian dialect, uniquely designed to understand and generate texts written in both Arabic and Latin scripts. Specifically, with Nile-Chat-3x4B-A6B, we introduce a novel language adaptation approach by leveraging the Branch-Train-MiX strategy to merge script-specialized experts, into a single MoE model. Our Nile-Chat models significantly outperform leading multilingual and Arabic LLMs, such as LLaMa, Jais, and ALLaM, on our newly introduced Egyptian evaluation benchmarks, which span both understanding and generative tasks. Notably, our 12B model yields a 14.4% performance gain over Qwen2.5-14B-Instruct on Latin-script benchmarks. All our resources are publicly available. We believe this work presents a comprehensive methodology for adapting LLMs to dual-script languages, addressing an often overlooked aspect in modern LLM development.