collaborators

15 papers

cs.CL2026

The Alignment Veto: How Safety Training Suppresses Cultural Knowledge in LLMs

Pardis Sadat Zahraei, Gokhan Tur, Dilek Hakkani-Tür +1

What happens inside a language model when alignment training conflicts with a cultural value it encodes? Across 16 MENA countries, 26 models, and 1.53M human survey responses, we s…

cs.CL2026

EiCAP: Beyond Fluency, Probing and Improving Emotional Intelligence in LLMs via Psychologically Grounded Multi-Turn Dialogue

Nizi Nazar, Pardis Sadat Zahraei, Dilek Hakkani-Tür +2

Large Language Models increasingly serve in emotionally sensitive roles, including mental health support, education, and crisis response, yet they lack a principled framework for a…

cs.CV2026

Almieyar-Oryx-BloomBench: A Bilingual Multimodal Benchmark for Cognitively Informed Evaluation of Vision-Language Models

Mohammad Mahdi Abootorabi, Omid Ghahroodi, Anas Madkoor +4

Despite the rapid progress of Vision-Language Models (VLMs), the field lacks benchmarks that rigorously diagnose their true reasoning abilities and chart meaningful progress toward…

cs.CL2026

Fanar 2.0: Arabic Generative AI Stack

FANAR TEAM, Ummar Abbas, Mohammad Shahmeer Ahmad +34

We present Fanar 2.0, the second generation of Qatar's Arabic-centric Generative AI platform. Sovereignty is a first-class design principle: every component, from data pipelines to…

cs.CL2026

The Judge Who Never Admits: Hidden Shortcuts in LLM-based Evaluation

Arash Marioriyad, Omid Ghahroodi, Ehsaneddin Asgari +2

Large language models (LLMs) are increasingly used as automatic judges to evaluate system outputs in tasks such as reasoning, question answering, and creative writing. A faithful j…

cs.CV2026

Eye-Q: A Multilingual Benchmark for Visual Word Puzzle Solving and Image-to-Phrase Reasoning

Ali Najar, Alireza Mirrokni, Arshia Izadyari +5

Vision-Language Models (VLMs) have achieved strong performance on standard vision-language benchmarks, yet often rely on surface-level recognition rather than deeper reasoning. We…