activity
20162026
most citedArabic Offensive Language on Twitter: Analysis and Experiments

86 citations · 332 across the 36 of their papers we have counts for

collaborators

45 papers

cs.CL2026

AraYoungVoices: A Diverse L1/L2 Corpus of Arabic Child and Adolescent Speech

Shammur Absar Chowdhury, Zien Sheikh Ali, Houssam Eddine-Othman Lachemat +1

State-of-the-art ASR systems primarily target native adult speech, leading to substantial performance gaps for children, adolescents, and L2 speakers. We introduce AraYoungVoices,…

cs.CL2026

Almieyar: A Culturally Grounded Benchmark for Multi-Dialect Arabic Speech Recognition

Omid Ghahroodi, Anas Madkoor, Dima Faris Al Saudi +37

Arabic speech technology has largely focused on Modern Standard Arabic, leaving the living dialects spoken by hundreds of millions under-served. We introduce ALMIEYAR, a culturally…

cs.CL2026

ArGuard Shared Task: Harmful Content Detection in Arabic Memes and LLM Prompts

Firoj Alam, Md. Rafiul Biswas, Mohamed Bayan Kmainasi +5

ArGuard is a shared task on harmful content detection in Arabic memes and LLM prompts. It includes two tracks: Track A focuses on multimodal hate detection in Arabic memes, while T…

cs.CY2026

Beyond Cultural Knowledge: Evaluating Arabic Cultural Appropriateness of Large Language Models

Enes Altinisik, Hamdy Mubarak, Masoomali Fatehkia +1

Large language models (LLMs) increasingly serve users whose expectations are shaped by their cultural context, yet most cultural evaluations test what a model knows rather than how…

cs.CV2026

When Do VLMs Help Arabic Manuscript OCR? A Cross-Dataset Study

Moshiur Farazi, Firoj Alam, Abderrahmane Maaradji +3

Vision-language models (VLMs) are increasingly being used for document understanding, yet their role in Arabic and Islamic manuscript recognition remains underexplored. To address…

cs.SD2026

WASIL: In-the-Wild Arabic Spoken Interactions with LLMs

Zien Sheikh Ali, Hamdy Mubarak, Soon-Gyo Jung +3

Large Language Models (LLMs) voice assistants are commonly built as cascaded Automatic Speech recognition (ASR) to LLM systems, where recognition errors can distort user intent. Di…