14 citations · 34 across the 14 of their papers we have counts for
15 papers · 1 filter
ImageEval 2026: Culturally Grounded Arabic Multimodal Evaluation
Samir Abdaljalil, Hunzalah Hassan Bhatti, Ahlam Bashiti +11
We present an overview of the ImageEval 2026 shared task on culturally grounded Arabic multimodal evaluation. It includes two tasks: (i) AynVQA, covering spoken visual question ans…
Said Aloud, Read Different: Cross-Modal Instability in Multimodal Models
Basel Mousi, Fahim Dalvi, Shammur Chowdhury +2
Multimodal foundation models are increasingly used in speech-first assistants that must interpret spoken queries and produce visually grounded decisions. Yet it remains unclear whe…
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…
Once Correct, Still Wrong: Counterfactual Hallucination in Multilingual Vision-Language Models
Basel Mousi, Fahim Dalvi, Shammur Chowdhury +2
Vision-language models (VLMs) can achieve high accuracy while still accepting culturally plausible but visually incorrect interpretations. Existing hallucination benchmarks rarely…
OASIS: A Multilingual and Multimodal Dataset for Culturally Grounded Spoken Visual QA
Firoj Alam, Ali Ezzat Shahroor, Md. Arid Hasan +8
Large-scale multimodal models achieve strong results on tasks like Visual Question Answering (VQA), but they are often limited when queries require cultural and visual information,…
An Exploration of Knowledge Editing for Arabic
Basel Mousi, Nadir Durrani, Fahim Dalvi
While Knowledge Editing (KE) has been widely explored in English, its behavior in morphologically rich languages like Arabic remains underexamined. In this work, we present the fir…
From Words to Waves: Analyzing Concept Formation in Speech and Text-Based Foundation Models
Asım Ersoy, Basel Mousi, Shammur Chowdhury +3
The emergence of large language models (LLMs) has demonstrated that systems trained solely on text can acquire extensive world knowledge, develop reasoning capabilities, and intern…
Editing Across Languages: A Survey of Multilingual Knowledge Editing
Nadir Durrani, Basel Mousi, Fahim Dalvi
While Knowledge Editing has been extensively studied in monolingual settings, it remains underexplored in multilingual contexts. This survey systematizes recent research on Multili…
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…
AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs
Basel Mousi, Nadir Durrani, Fatema Ahmad +6
Arabic, with its rich diversity of dialects, remains significantly underrepresented in Large Language Models, particularly in dialectal variations. We address this gap by introduci…
Exploring Alignment in Shared Cross-lingual Spaces
Basel Mousi, Nadir Durrani, Fahim Dalvi +2
Despite their remarkable ability to capture linguistic nuances across diverse languages, questions persist regarding the degree of alignment between languages in multilingual embed…
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…
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…
Can LLMs facilitate interpretation of pre-trained language models?
Basel Mousi, Nadir Durrani, Fahim Dalvi
Work done to uncover the knowledge encoded within pre-trained language models rely on annotated corpora or human-in-the-loop methods. However, these approaches are limited in terms…
On the Evaluation of the Plausibility and Faithfulness of Sentiment Analysis Explanations
Julia El Zini, Mohamad Mansour, Basel Mousi +1
Current Explainable AI (ExAI) methods, especially in the NLP field, are conducted on various datasets by employing different metrics to evaluate several aspects. The lack of a comm…