5 citations · 7 across the 11 of their papers we have counts for
12 papers
Geometric Parrots: Rule Absence vs. Rule Fragility in Spatial and Physical Reasoning for Vision-Language Models
Bilal Jawaid, Hamza Hanif, Muhammad Maaz Uddin +8
Vision-language models (VLMs) can answer many geometric and physical reasoning questions correctly, yet still behave inconsistently in interaction, for example, abandoning a correc…
Do Medical Vision Language Models Actually See? A Counterfactual Grounding Framework and Hard-Negative Contrastive Training for Visually-Reliant Medical VLMs
Anas Zafar, Leema Krishna Murali, Siddhant Bharadwaj +2
Large vision language models (VLMs) report strong accuracy on medical question-answering, yet it remains unclear whether they reason from visual evidence or exploit textual shortcu…
Medmarks: A Comprehensive Open-Source LLM Benchmark Suite for Medical Tasks
Benjamin Warner, Ratna Sagari Grandhi, Max Kieffer +32
Evaluating large language models (LLMs) for medical applications remains challenging due to benchmark saturation, limited data accessibility, and insufficient coverage of relevant…
Towards Responsible Multimodal Medical Reasoning via Context-Aligned Vision-Language Models
Sumra Khan, Sagar Chhabriya, Aizan Zafar +5
Medical vision-language models (VLMs) show strong performance on radiology tasks but often produce fluent yet weakly grounded conclusions due to over-reliance on a dominant modalit…
Projection Guided Personalized Federated Learning for Low Dose CT Denoising
Anas Zafar, Muhammad Waqas, Amgad Muneer +2
Low-dose CT (LDCT) reduces radiation exposure but introduces protocol-dependent noise and artifacts that vary across institutions. While federated learning enables collaborative tr…
Beyond Accuracy: Evaluating Visual Grounding In Multimodal Medical Reasoning
Anas Zafar, Leema Krishna Murali, Ashish Vashist
Recent work shows that text-only reinforcement learning with verifiable rewards (RLVR) can match or outperform image-text RLVR on multimodal medical VQA benchmarks, suggesting curr…
Beyond Anatomy: Explainable ASD Classification from rs-fMRI via Functional Parcellation and Graph Attention Networks
Syeda Hareem Madani, Noureen Bibi, Adam Rafiq Jeraj +3
Anatomical brain parcellations dominate rs-fMRI-based Autism Spectrum Disorder (ASD) classification, yet their rigid boundaries may fail to capture the idiosyncratic connectivity p…
CARL-CXR: Continual Adapter-Based Routing for Task-Unknown Chest Radiograph Classification
Muthu Subash Kavitha, Anas Zafar, Amgad Muneer +1
Clinical deployment of chest radiograph classifiers requires models that can be updated as new datasets become available without retraining on previously observed data or degrading…
The Next Layer: Augmenting Foundation Models with Structure-Preserving and Attention-Guided Learning for Local Patches to Global Context Awareness in Computational Pathology
Muhammad Waqas, Rukhmini Bandyopadhyay, Eman Showkatian +12
Foundation models have recently emerged as powerful feature extractors in computational pathology, yet they typically omit mechanisms for leveraging the global spatial structure of…
Evaluating Multimodal Large Language Models on Educational Textbook Question Answering
Hessa A. Alawwad, Anas Zafar, Areej Alhothali +3
Multimodal large language models (MLLMs) have shown success in vision-language tasks, but their ability to reason over complex educational materials remains largely untested. This…
Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact
Rizwan Qureshi, Ranjan Sapkota, Abbas Shah +16
Can machines truly think, reason and act in domains like humans? This enduring question continues to shape the pursuit of Artificial General Intelligence (AGI). Despite the growing…
Who is Responsible? The Data, Models, Users or Regulations? A Comprehensive Survey on Responsible Generative AI for a Sustainable Future
Shaina Raza, Rizwan Qureshi, Anam Zahid +14
Generative AI is rapidly moving from research to deployment, elevating the need for responsible development, evaluation, and governance. We conduct a PRISMA guided review of 232 st…