23 citations · 52 across the 19 of their papers we have counts for
3 papers · 1 filter
VAuLT: Augmenting the Vision-and-Language Transformer for Sentiment Classification on Social Media
Georgios Chochlakis, Tejas Srinivasan, Jesse Thomason +1
We propose the Vision-and-Augmented-Language Transformer (VAuLT). VAuLT is an extension of the popular Vision-and-Language Transformer (ViLT), and improves performance on vision-an…
Curriculum Learning for Data-Efficient Vision-Language Alignment
Tejas Srinivasan, Xiang Ren, Jesse Thomason
Aligning image and text encoders from scratch using contrastive learning requires large amounts of paired image-text data. We alleviate this need by aligning individually pre-train…
CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks
Tejas Srinivasan, Ting-Yun Chang, Leticia Leonor Pinto Alva +3
Current state-of-the-art vision-and-language models are evaluated on tasks either individually or in a multi-task setting, overlooking the challenges of continually learning (CL) t…