Srijita Karmakar was recognized with the 2026 FoVea Travel and Networking Award. Sana Shehabi was awarded the very competitive National Science Foundation Graduate Research Fellow.
INTERLACE removes 25% of a vision-language model's layers while keeping about 89% of its performance in challenging benchmarks.
From eye movements to faces and gaze-following to the influence of retinal deficits on scene understanding
The type of vision loss can impact what you see and where you look in different ways
Learned foveal representations, not gaze-mediated information access, underlie perceptual advantages for canonical face configurations
The presence of a foveal gazer meaningfully improves accuracy in locating a gaze goal far in the periphery
Analyizing the inner workings of CNNs to predict neuron types mediating covert attention
CNNs discount target-like structures of normal anatomic structures like radiologists do.
It might help explain attention-like behaviors in simple organisms from mice to fruit flies.
When and how AI helps radiologists. Answers from vision science.
