3 papers
cs.CV2025
INTERLACE: Interleaved Layer Pruning and Efficient Adaptation in Large Vision-Language Models
Parsa Madinei, Ryan Solgi, Ziqi Wen +3
We introduce INTERLACE, a novel framework that prunes redundant layers in VLMs while maintaining performance through sample-efficient finetuning. Existing layer pruning methods lea…
cs.CV2025
DReX: Pure Vision Fusion of Self-Supervised and Convolutional Representations for Image Complexity Prediction
Jonathan Skaza, Parsa Madinei, Ziqi Wen +1
Visual complexity prediction is a fundamental problem in computer vision with applications in image compression, retrieval, and classification. Understanding what makes humans perc…
cs.CV2025
Predicting Reaction Time to Comprehend Scenes with Foveated Scene Understanding Maps
Ziqi Wen, Jonathan Skaza, Shravan Murlidaran +2
Although models exist that predict human response times (RTs) in tasks such as target search and visual discrimination, the development of image-computable predictors for scene und…