collaborators

8 papers

cs.CL2025

AraLingBench A Human-Annotated Benchmark for Evaluating Arabic Linguistic Capabilities of Large Language Models

Mohammad Zbeeb, Hasan Abed Al Kader Hammoud, Sina Mukalled +5

We present AraLingBench: a fully human annotated benchmark for evaluating the Arabic linguistic competence of large language models (LLMs). The benchmark spans five core categories…

cs.CL2025

Hala Technical Report: Building Arabic-Centric Instruction & Translation Models at Scale

Hasan Abed Al Kader Hammoud, Mohammad Zbeeb, Bernard Ghanem

We present Hala, a family of Arabic-centric instruction and translation models built with our translate-and-tune pipeline. We first compress a strong AREN teacher…

cs.CL2025

Reasoning Vectors: Transferring Chain-of-Thought Capabilities via Task Arithmetic

Mohammad Zbeeb, Hasan Abed Al Kader Hammoud, Bernard Ghanem

Large language models often require costly optimization, such as reinforcement learning, to master complex reasoning tasks. This work demonstrates that reasoning ability, once lear…

cs.CL2025

Train Long, Think Short: Curriculum Learning for Efficient Reasoning

Hasan Abed Al Kader Hammoud, Kumail Alhamoud, Abed Hammoud +3

Recent work on enhancing the reasoning abilities of large language models (LLMs) has introduced explicit length control as a means of constraining computational cost while preservi…

cs.CL2025

An Embarrassingly Simple Defense Against LLM Abliteration Attacks

Harethah Abu Shairah, Hasan Abed Al Kader Hammoud, Bernard Ghanem +1

Large language models (LLMs) are typically aligned to refuse harmful instructions through safety fine-tuning. A recent attack, termed abliteration, identifies and suppresses the si…

cs.CL2025

Beyond the Last Answer: Your Reasoning Trace Uncovers More than You Think

Hasan Abed Al Kader Hammoud, Hani Itani, Bernard Ghanem

Large Language Models (LLMs) leverage step-by-step reasoning to solve complex problems. Standard evaluation practice involves generating a complete reasoning trace and assessing th…