Efficient Multimodal Learning With Pre-Trained Models On Single GPU

This is a Plain English Papers summary of a research paper called Efficient Multimodal Learning Using Pre-Trained Models on a Single GPU. If you like these kinds of analysis, you should join AImodels.fyi or follow me on Twitter.

  
  
  Overview

The goal of multimodal alignment is to learn a single shared latent space between different input modalities, like images and text.
Current powerful multimodal models require massive datasets and computational resources to train, making them inaccessible for many practical use cases.
The authors propose FuseMix, a multimodal augmentation technique th...