4 papers
Do VLMs Perceive or Recall? Probing Visual Perception vs. Memory with Classic Visual Illusions
Xiaoxiao Sun, Mingyang Li, Kun Yuan +7
Large Vision-Language Models (VLMs) often answer classic visual illusions "correctly" on original images, yet persist with the same responses when illusion factors are inverted, ev…
Downscaling Intelligence: Exploring Perception and Reasoning Bottlenecks in Small Multimodal Models
Mark Endo, Serena Yeung-Levy
Scaling up multimodal models has enabled remarkable advances in visual understanding and reasoning, but practical demands call for smaller, efficient systems. In this work, we cond…
Feather the Throttle: Revisiting Visual Token Pruning for Vision-Language Model Acceleration
Mark Endo, Xiaohan Wang, Serena Yeung-Levy
Recent works on accelerating Vision-Language Models achieve strong performance across a variety of vision-language tasks despite highly compressing visual information. In this work…
Systematic Evaluation of Large Vision-Language Models for Surgical Artificial Intelligence
Anita Rau, Mark Endo, Josiah Aklilu +6
Large Vision-Language Models offer a new paradigm for AI-driven image understanding, enabling models to perform tasks without task-specific training. This flexibility holds particu…