4 citations · 4 across the 12 of their papers we have counts for
16 papers
AraModernBERT: Transtokenized Initialization and Long-Context Encoder Modeling for Arabic
Omar Elshehy, Omer Nacar, Abdelbasset Djamai +3
Encoder-only transformer models remain widely used for discriminative NLP tasks, yet recent architectural advances have largely focused on English. In this work, we present AraMode…
ASCAT: An Arabic Scientific Corpus and Benchmark for Advanced Translation Evaluation
Serry Sibaee, Khloud Al Jallad, Zineb Yousfi +4
We present ASCAT (Arabic Scientific Corpus for Advanced Translation), a high-quality English-Arabic parallel benchmark corpus designed for scientific translation evaluation constru…
From Language to Action in Arabic: Reliable Structured Tool Calling via Data-Centric Fine-Tuning
Omer Nacar, Deema Alquffari, Saleh Alsharideh +22
Function-calling language models are essential for agentic AI systems that translate natural language into executable structured actions, yet existing models exhibit severe structu…
ARCADE: A City-Scale Corpus for Fine-Grained Arabic Dialect Tagging
Omer Nacar, Serry Sibaee, Adel Ammar +12
The Arabic language is characterized by a rich tapestry of regional dialects that differ substantially in phonetics and lexicon, reflecting the geographic and cultural diversity of…
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…
UI-Level Evaluation of ALLaM 34B: Measuring an Arabic-Centric LLM via HUMAIN Chat
Omer Nacar
Large language models (LLMs) trained primarily on English corpora often struggle to capture the linguistic and cultural nuances of Arabic. To address this gap, the Saudi Data and A…