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Found 2 papers, 1 papers with code
TIBET: Identifying and Evaluating Biases in Text-to-Image Generative Models
Text-to-Image (TTI) generative models have shown great progress in the past few years in terms of their ability to generate complex and high-quality imagery.
VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge
In contrast to previous methods which inject knowledge from static knowledge bases, we investigate the incorporation of contextualized knowledge using Commonsense Transformer (COMET), an existing knowledge model trained on human-curated knowledge bases.
Ranked #8 on
Visual Question Answering (VQA)
on A-OKVQA
(DA VQA Score metric)
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