1 citations · 2 across the 8 of their papers we have counts for
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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…
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…
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…
Commonsense Reasoning in Arab Culture
Abdelrahman Sadallah, Junior Cedric Tonga, Khalid Almubarak +7
Despite progress in Arabic large language models, such as Jais and AceGPT, their evaluation on commonsense reasoning has largely relied on machine-translated datasets, which lack c…
Casablanca: Data and Models for Multidialectal Arabic Speech Recognition
Bashar Talafha, Karima Kadaoui, Samar Mohamed Magdy +24
In spite of the recent progress in speech processing, the majority of world languages and dialects remain uncovered. This situation only furthers an already wide technological divi…
ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic
Fajri Koto, Haonan Li, Sara Shatnawi +10
The focus of language model evaluation has transitioned towards reasoning and knowledge-intensive tasks, driven by advancements in pretraining large models. While state-of-the-art…
Automatic Restoration of Diacritics for Speech Data Sets
Sara Shatnawi, Sawsan Alqahtani, Hanan Aldarmaki
Automatic text-based diacritic restoration models generally have high diacritic error rates when applied to speech transcripts as a result of domain and style shifts in spoken lang…
ClArTTS: An Open-Source Classical Arabic Text-to-Speech Corpus
Ajinkya Kulkarni, Atharva Kulkarni, Sara Abedalmonem Mohammad Shatnawi +1
At present, Text-to-speech (TTS) systems that are trained with high-quality transcribed speech data using end-to-end neural models can generate speech that is intelligible, natural…