10 papers
From Observation to Intervention: Memory in Brains and Large Language Models
Morteza Salehjahromi, Shayan A. Zadegan, Amgad Muneer +1
Brains and large language models (LLMs) are fundamentally different memory systems, but they can be compared through shared functional questions: where memory-related information i…
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…
Foundation Models in Biomedical Imaging: Turning Hype into Reality
Amgad Muneer, Kai Zhang, Ibraheem Hamdi +6
Foundation models (FMs) are driving a prominent shift in biomedical imaging from task-specific models to unified backbone models for diverse tasks. This opens an avenue to integrat…
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…
Temperature-Dependent Performance of Prompting Strategies in Extended Reasoning Large Language Models
Mousa Salah, Amgad Muneer
Extended reasoning models represent a transformative shift in Large Language Model (LLM) capabilities by enabling explicit test-time computation for complex problem solving. Howeve…
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…