2 citations · 3 across the 7 of their papers we have counts for
7 papers · 1 filter
Vibe Spaces for Creatively Connecting and Expressing Visual Concepts
Huzheng Yang, Katherine Xu, Andrew Lu +3
Creating new visual concepts often requires connecting distinct ideas through their most relevant shared attributes -- their vibe. We introduce Vibe Blending, a novel task for gene…
Artifacts and Attention Sinks: Structured Approximations for Efficient Vision Transformers
Andrew Lu, Wentinn Liao, Liuhui Wang +2
Vision transformers have emerged as a powerful tool across a wide range of applications, yet their inner workings remain only partially understood. In this work, we examine the phe…
"I Know It When I See It": Mood Spaces for Connecting and Expressing Visual Concepts
Huzheng Yang, Katherine Xu, Michael D. Grossberg +2
Expressing complex concepts is easy when they can be labeled or quantified, but many ideas are hard to define yet instantly recognizable. We propose a Mood Board, where users conve…
AlignedCut: Visual Concepts Discovery on Brain-Guided Universal Feature Space
Huzheng Yang, James Gee, Jianbo Shi
We study the intriguing connection between visual data, deep networks, and the brain. Our method creates a universal channel alignment by using brain voxel fMRI response prediction…
Brain Decodes Deep Nets
Huzheng Yang, James Gee, Jianbo Shi
We developed a tool for visualizing and analyzing large pre-trained vision models by mapping them onto the brain, thus exposing their hidden inside. Our innovation arises from a su…
Memory Encoding Model
Huzheng Yang, James Gee, Jianbo Shi
We explore a new class of brain encoding model by adding memory-related information as input. Memory is an essential brain mechanism that works alongside visual stimuli. During a v…