37 citations · 65 across the 4 of their papers we have counts for
4 papers
An Introduction to Vision-Language Modeling
Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay +38
Following the recent popularity of Large Language Models (LLMs), several attempts have been made to extend them to the visual domain. From having a visual assistant that could guid…
Modeling Caption Diversity in Contrastive Vision-Language Pretraining
Samuel Lavoie, Polina Kirichenko, Mark Ibrahim +4
There are a thousand ways to caption an image. Contrastive Language Pretraining (CLIP) on the other hand, works by mapping an image and its caption to a single vector -- limiting h…
Understanding the Detrimental Class-level Effects of Data Augmentation
Polina Kirichenko, Mark Ibrahim, Randall Balestriero +4
Data augmentation (DA) encodes invariance and provides implicit regularization critical to a model's performance in image classification tasks. However, while DA improves average a…
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
Micah Goldblum, Hossein Souri, Renkun Ni +10
Neural network based computer vision systems are typically built on a backbone, a pretrained or randomly initialized feature extractor. Several years ago, the default option was an…