1 citations · 1 across the 14 of their papers we have counts for
4 papers · 2 filters
T3: Test-Time Model Merging in VLMs for Zero-Shot Medical Imaging Analysis
Raza Imam, Hu Wang, Dwarikanath Mahapatra +1
In medical imaging, vision-language models face a critical duality: pretrained networks offer broad robustness but lack subtle, modality-specific characteristics, while fine-tuned…
Decoupling Clinical and Class-Agnostic Features for Reliable Few-Shot Adaptation under Shift
Umaima Rahman, Raza Imam, Mohammad Yaqub +1
Medical vision-language models (VLMs) offer promise for clinical decision support, yet their reliability under distribution shifts remains a major concern for safe deployment. Thes…
On the Robustness of Medical Vision-Language Models: Are they Truly Generalizable?
Raza Imam, Rufael Marew, Mohammad Yaqub
Medical Vision-Language Models (MVLMs) have achieved par excellence generalization in medical image analysis, yet their performance under noisy, corrupted conditions remains largel…
Noise is an Efficient Learner for Zero-Shot Vision-Language Models
Raza Imam, Asif Hanif, Jian Zhang +3
Recently, test-time adaptation has garnered attention as a method for tuning models without labeled data. The conventional modus operandi for adapting pre-trained vision-language m…