9 citations · 34 across the 27 of their papers we have counts for
5 papers · 2 filters
C-GAP: Class-Aware and Online Prompting Improves Vision-Language Models on Imbalanced Classes
Francis Fernandez, Arash Jahangiri, Salimeh Sekeh
Safety-critical perception systems must reliably detect rare object classes within small label spaces, a setting that long-tailed detection methods, designed for hundreds of classe…
Cross-Contextual Vision-Language Adaptation with LoRA for Personalized Severe Adverse Event Detection in Clinical Wound Monitoring
Aditi Naiknaware, Jian Sun, Aminreza Khandan +4
Wound monitoring is a critical yet underserved clinical challenge, where timely identification of severe adverse events (SAEs) such as infection, tissue deterioration, and delayed…
Theoretical Grounding of Out-Of-Distribution Detection With Reinforcement Learning Optimizer
Salimeh Sekeh, Xin Zhang
Out-of-distribution (OOD) detection in dynamic open-world environments requires a model to continually adapt to evolving data distributions while generalizing to covariate-shifted…
Understanding Cross-Modal Contributions in Continual Vision-Language Models: A Theoretical Perspective
Salimeh Sekeh, Mary Wisell
Continual vision-language models are commonly addressed through sequential fine-tuning; however, although this paradigm enables adaptation to new environments (tasks), it inherentl…
T-QPM: Enabling Temporal Out-Of-Distribution Detection and Domain Generalization for Vision-Language Models in Open-World
Aditi Naiknaware, Salimeh Sekeh
Out-of-distribution (OOD) detection remains a critical challenge in open-world learning, where models must adapt to evolving data distributions. While recent vision-language models…