1 citations · 1 across the 4 of their papers we have counts for
4 papers
SABRE: A Multi-Agent Approach for Selecting Out-of-Distribution Detectors Under a Budget
Mary Wisell, Salimeh Sekeh
Post-hoc out-of-distribution (OOD) detection for vision-language models assumes that a detector chosen on a benchmark stays reliable once deployed. We show this fails across domain…
GRASP: Gradient-Aligned Sequential Parameter Transfer for Memory-Efficient Multi-Source Learning
Mary Isabelle Wisell, Nicholas Jacobs, Aayush Manandhar +1
Multi-source transfer learning faces a fundamental scalability bottleneck: existing approaches require either loading all K source models into memory simultaneously during paramete…
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…
Ghost-Connect Net: A Generalization-Enhanced Guidance For Sparse Deep Networks Under Distribution Shifts
Mary Isabelle Wisell, Salimeh Yasaei Sekeh
Sparse deep neural networks (DNNs) excel in real-world applications like robotics and computer vision, by reducing computational demands that hinder usability. However, recent stud…