8 citations · 10 across the 10 of their papers we have counts for
3 papers · 1 filter
SAT: Dynamic Spatial Aptitude Training for Multimodal Language Models
Arijit Ray, Jiafei Duan, Ellis Brown +9
Reasoning about motion and space is a fundamental cognitive capability that is required by multiple real-world applications. While many studies highlight that large multimodal lang…
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models
Matt Deitke, Christopher Clark, Sangho Lee +47
Today's most advanced vision-language models (VLMs) remain proprietary. The strongest open-weight models rely heavily on synthetic data from proprietary VLMs to achieve good perfor…
Seeing the Unseen: Visual Common Sense for Semantic Placement
Ram Ramrakhya, Aniruddha Kembhavi, Dhruv Batra +3
Computer vision tasks typically involve describing what is present in an image (e.g. classification, detection, segmentation, and captioning). We study a visual common sense task t…