3 papers
cs.CV2026
Video Models Reason Early: Exploiting Plan Commitment for Maze Solving
Kaleb Newman, Tyler Zhu, Olga Russakovsky
Video diffusion models exhibit emergent reasoning capabilities like solving mazes and puzzles, yet little is understood about how they reason during generation. We take a first ste…
cs.CV2026
GASS: Geometry-Aware Spherical Sampling for Disentangled Diversity Enhancement in Text-to-Image Generation
Ye Zhu, Kaleb S. Newman, Johannes F. Lutzeyer +3
Despite high semantic alignment, modern text-to-image (T2I) generative models still struggle to synthesize diverse images from a given prompt. In this work, we enhance the T2I dive…
cs.CV2024
Do Pre-trained Vision-Language Models Encode Object States?
Kaleb Newman, Shijie Wang, Yuan Zang +2
For a vision-language model (VLM) to understand the physical world, such as cause and effect, a first step is to capture the temporal dynamics of the visual world, for example how…