activity
20182026
most citedLAraBench: Benchmarking Arabic AI with Large Language Models

14 citations · 46 across the 18 of their papers we have counts for

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9 papers · 1 filter

cs.CL2026

Latent Mechanisms of Language Control in Multilingual Language Models

Ryo Mitsuhashi, Sabri Boughorbel, Majd Hawasly

Multilingual large language models can exhibit unintended code-switching -- unnecessarily alternating between languages during generation. We present a comparative study of three m…

cs.CL2026

There Is More to Refusal in Large Language Models than a Single Direction

Faaiz Joad, Majd Hawasly, Sabri Boughorbel +2

Prior work argues that refusal in large language models is mediated by a single direction, enabling steering and abliteration. We show that this account is incomplete: across diver…

cs.CL2025

Beyond the Leaderboard: Understanding Performance Disparities in Large Language Models via Model Diffing

Sabri Boughorbel, Fahim Dalvi, Nadir Durrani +1

As fine-tuning becomes the dominant paradigm for improving large language models (LLMs), understanding what changes during this process is increasingly important. Traditional bench…

cs.CL2025★ 5 cited

Fanar: An Arabic-Centric Multimodal Generative AI Platform

Fanar Team, Ummar Abbas, Mohammad Shahmeer Ahmad +39

We present Fanar, a platform for Arabic-centric multimodal generative AI systems, that supports language, speech and image generation tasks. At the heart of Fanar are Fanar Star an…

cs.CL2024

Improving Language Models Trained on Translated Data with Continual Pre-Training and Dictionary Learning Analysis

Sabri Boughorbel, MD Rizwan Parvez, Majd Hawasly

Training LLMs for low-resource languages usually utilizes data augmentation from English using machine translation (MT). This, however, brings a number of challenges to LLM trainin…

cs.CL2023★ 2 cited

Analyzing Multilingual Competency of LLMs in Multi-Turn Instruction Following: A Case Study of Arabic

Sabri Boughorbel, Majd Hawasly

While significant progress has been made in benchmarking Large Language Models (LLMs) across various tasks, there is a lack of comprehensive evaluation of their abilities in respon…

cs.CL2023★ 4 cited

LLMeBench: A Flexible Framework for Accelerating LLMs Benchmarking

Fahim Dalvi, Maram Hasanain, Sabri Boughorbel +10

The recent development and success of Large Language Models (LLMs) necessitate an evaluation of their performance across diverse NLP tasks in different languages. Although several…

cs.CL2023★ 14 cited

LAraBench: Benchmarking Arabic AI with Large Language Models

Ahmed Abdelali, Hamdy Mubarak, Shammur Absar Chowdhury +13

Recent advancements in Large Language Models (LLMs) have significantly influenced the landscape of language and speech research. Despite this progress, these models lack specific b…

cs.CL2023★ 1 cited

Multi-Modal Perceiver Language Model for Outcome Prediction in Emergency Department

Sabri Boughorbel, Fethi Jarray, Abdulaziz Al Homaid +2

Language modeling have shown impressive progress in generating compelling text with good accuracy and high semantic coherence. An interesting research direction is to augment these…