FLAVA: A Foundational Language And Vision Alignment Model

Meta (Israel)

Indexed incrossref

Abstract

State-of-the-art vision and vision-and-language models rely on large-scale visio-linguistic pretraining for obtaining good performance on a variety of downstream tasks. Generally, such models are often either cross-modal (contrastive) or multi-modal (with earlier fusion) but not both; and they often only target specific modalities or tasks. A promising direction would be to use a single holistic universal model, as a “foundation”, that targets all modalities at once-a true vision and language foundation model should be good at vision tasks, language tasks, and cross- and multi-modal vision and language tasks. We introduce FLAVA as such a model and demonstrate impressive performance on a wide range of 35 tasks…

Citation impact

487
total citations
FWCI
27.03
Percentile
100%
References
169
Citations per year

Authors

7

Topics & keywords

Keywords
  • Computer science
  • Vision science
  • Artificial intelligence
  • Natural language processing
  • Cognitive science
  • Linguistics
  • Psychology
  • Philosophy
No related works found for this paper.