1 citations · 2 across the 18 of their papers we have counts for
18 papers
Aslema at NADI 2026: Data Augmentation for Intent Recognition and Slot Filling
Tajwaar Shafiq, Hunzalah Hassan Bhatti, Firoj Alam +1
We present Aslema, our system for NADI 2026 Shared Task 5, which consists of two subtasks: intent recognition and slot filling. We evaluate four omni LLMs in a zero-shot setting an…
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…
Multi-turn Conversational AI from Text to Multimodal Interaction: Data, Models, Evaluation, and Open Challenges
Syeda Faiza Ahmed, Syeda Faiza Ahmed Sara, Zien Sheikh Ali +3
Conversational AI is moving beyond isolated text prompts toward sustained, multimodal interaction. In real conversations, users clarify goals, revise requests, interrupt responses,…
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…
Multilingual and Multimodal LLMs in the Wild: Building for Low-Resource Languages
Firoj Alam, Shammur Absar Chowdhury, Enamul Hoque Prince
Multimodal LLMs are evolving from vision-language to tri-modality that see, hear, and read, yet pipelines and benchmarks remain English-centric and compute-heavy. The tutorial offe…
Beyond LLM-as-a-Judge: Deterministic Metrics for Multilingual Generative Text Evaluation
Firoj Alam, Gagan Bhatia, Sahinur Rahman Laskar +1
While Large Language Models (LLMs) are increasingly adopted as automated judges for evaluating generated text, their outputs are often costly, and highly sensitive to prompt design…
CoCR-RAG: Enhancing Retrieval-Augmented Generation in Web Q&A via Concept-oriented Context Reconstruction
Kaize Shi, Xueyao Sun, Qika Lin +4
Retrieval-augmented generation (RAG) has shown promising results in enhancing Q&A by incorporating information from the web and other external sources. However, the supporting docu…
Fanar-Sadiq: A Multi-Agent Architecture for Grounded Islamic QA
Ummar Abbas, Mourad Ouzzani, Mohamed Y. Eltabakh +7
Large language models (LLMs) can answer religious knowledge queries fluently, yet they often hallucinate and misattribute sources, which is especially consequential in Islamic sett…
MENASpeechBank: A Reference Voice Bank with Persona-Conditioned Multi-Turn Conversations for AudioLLMs
Zien Sheikh Ali, Hunzalah Hassan Bhatti, Rabindra Nath Nandi +2
Audio large language models (AudioLLMs) enable instruction following over speech and general audio, but progress is limited by the scarcity of diverse, conversational, and instruct…
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…
Multi-Task Instruction Tuning via Data Scheduling for Low-Resource Arabic SpeechLLMs
Hunzalah Hassan Bhatti, Firoj Alam, Shammur Absar Chowdhury
Audio large language models (LLMs) enable unified speech understanding and generation, but adapting them to linguistically complex and dialect-rich settings such as Arabic-English…
From RAG to Agentic RAG for Faithful Islamic Question Answering
Gagan Bhatia, Hamdy Mubarak, Mustafa Jarrar +8
Large Language Models (LLMs) are increasingly used for Islamic question answering, where ungrounded responses may carry serious religious consequences. Yet standard MCQ/MRC-style e…
Beyond MCQ: An Open-Ended Arabic Cultural QA Benchmark with Dialect Variants
Hunzalah Hassan Bhatti, Firoj Alam
Large Language Models (LLMs) are increasingly used to answer everyday questions, yet their performance on culturally grounded and dialectal content remains uneven across languages.…
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,…
The Landscape of Arabic Large Language Models (ALLMs): A New Era for Arabic Language Technology
Shahad Al-Khalifa, Nadir Durrani, Hend Al-Khalifa +1
The emergence of ChatGPT marked a transformative milestone for Artificial Intelligence (AI), showcasing the remarkable potential of Large Language Models (LLMs) to generate human-l…
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…
NativQA Framework: Enabling LLMs and VLMs with Native, Local, and Everyday Knowledge
Firoj Alam, Md Arid Hasan, Sahinur Rahman Laskar +3
The rapid progress of large language models (LLMs) raises concerns about cultural bias, fairness, and performance in diverse languages and underrepresented regions. Addressing thes…