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cs.CL2026
Arabic Safety Alignment as Selective Refusal: An Empirical Study of SFT, DPO, and Guard Calibration
Mohamad Zbib, Ammar Mohanna
Arabic large language models must refuse harmful prompts without over-refusing benign or sensitive prompts, yet a single refusal rate hides this trade-off. We evaluate it using ben…
cs.CL2026
TAPS: Task Aware Proposal Distributions for Speculative Sampling
Mohamad Zbib, Mohamad Bazzi, Ammar Mohanna +2
Speculative decoding accelerates autoregressive generation by letting a lightweight draft model propose future tokens that a larger target model then verifies in parallel. In pract…
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…