5 citations · 8 across the 14 of their papers we have counts for
9 papers · 1 filter
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…
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…
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…
Calibrated and Robust Foundation Models for Vision-Language and Medical Image Tasks Under Distribution Shift
Behraj Khan, Tahir Qasim Syed, Nouman M. Durrani +3
Foundation models like CLIP and SAM have advanced computer vision and medical imaging via low-shot transfer learning, aiding CADD with limited data. However, their deployment faces…
Leveraging MIMIC Datasets for Better Digital Health: A Review on Open Problems, Progress Highlights, and Future Promises
Afifa Khaled, Mohammed Sabir, Rizwan Qureshi +4
The Medical Information Mart for Intensive Care (MIMIC) datasets have become the Kernel of Digital Health Research by providing freely accessible, deidentified records from tens of…
A Layered Self-Supervised Knowledge Distillation Framework for Efficient Multimodal Learning on the Edge
Tarique Dahri, Zulfiqar Ali Memon, Zhenyu Yu +6
We introduce Layered Self-Supervised Knowledge Distillation (LSSKD) framework for training compact deep learning models. Unlike traditional methods that rely on pre-trained teacher…
SatelliteFormula: Multi-Modal Symbolic Regression from Remote Sensing Imagery for Physics Discovery
Zhenyu Yu, Mohd. Yamani Idna Idris, Pei Wang +3
We propose SatelliteFormula, a novel symbolic regression framework that derives physically interpretable expressions directly from multi-spectral remote sensing imagery. Unlike tra…
DanceText: A Training-Free Layered Framework for Controllable Multilingual Text Transformation in Images
Zhenyu Yu, Mohd Yamani Idna Idris, Hua Wang +6
We present DanceText, a training-free framework for multilingual text editing in images, designed to support complex geometric transformations and achieve seamless foreground-backg…
Confidence-calibrated covariate shift correction for few-shot classification in Vision-Language Models
Behraj Khan, Rizwan Qureshi, Nouman Muhammad Durrani +1
Since the establishment of vision-language foundation models as the new mainstay in low-shot vision classification tasks, the question of domain generalization arising from insuffi…