activity
20232026
most citedCasablanca: Data and Models for Multidialectal Arabic Speech Recognition

1 citations · 2 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CL2026

LQM: Linguistically Motivated Multidimensional Quality Metrics for Machine Translation

Samar M. Magdy, Fakhraddin Alwajih, Abdellah El Mekki +2

Existing MT evaluation frameworks, including automatic metrics and human evaluation schemes such as Multidimensional Quality Metrics (MQM), are largely language-agnostic. However,…

cs.CL2026

Alexandria: A Multi-Domain Dialectal Arabic Machine Translation Dataset for Culturally Inclusive and Linguistically Diverse LLMs

Abdellah El Mekki, Samar M. Magdy, Houdaifa Atou +44

Arabic is a highly diglossic language where most daily communication occurs in regional dialects rather than Modern Standard Arabic (MSA). Despite this, machine translation (MT) sy…

cs.CL2025

PalmX 2025: The First Shared Task on Benchmarking LLMs on Arabic and Islamic Culture

Fakhraddin Alwajih, Abdellah El Mekki, Hamdy Mubarak +3

Large Language Models (LLMs) inherently reflect the vast data distributions they encounter during their pre-training phase. As this data is predominantly sourced from the web, ther…

cs.CL2025

Pearl: A Multimodal Culturally-Aware Arabic Instruction Dataset

Fakhraddin Alwajih, Samar M. Magdy, Abdellah El Mekki +34

Mainstream large vision-language models (LVLMs) inherently encode cultural biases, highlighting the need for diverse multimodal datasets. To address this gap, we introduce PEARL, a…

cs.CL2025

Palm: A Culturally Inclusive and Linguistically Diverse Dataset for Arabic LLMs

Fakhraddin Alwajih, Abdellah El Mekki, Samar Mohamed Magdy +41

As large language models (LLMs) become increasingly integrated into daily life, ensuring their cultural sensitivity and inclusivity is paramount. We introduce our dataset, a year-l…

cs.CL2025

Jawaher: A Multidialectal Dataset of Arabic Proverbs for LLM Benchmarking

Samar M. Magdy, Sang Yun Kwon, Fakhraddin Alwajih +3

Recent advancements in instruction fine-tuning, alignment methods such as reinforcement learning from human feedback (RLHF), and optimization techniques like direct preference opti…