How does Flamingo's multimodal few-shot learning performance compare to GPT-4o on vision-language benchmarks l

Abstract

Abstract: Despite progress in perceptual tasks such as image classification, computers still perform poorly on cognitive tasks such as image description and question answering. Cognition is core to tasks that involve not just recognizing, but reasoning about our visual world. However, models used to tackle the rich content in images for cognitive tasks are still being trained using the same datasets designed for perceptual tasks. To achieve success at cognitive tasks, models need to understand the interactions and relationships between objects in an image. When asked ``What vehicle is the person riding?''

Research Question

How does Flamingo's multimodal few-shot learning performance compare to GPT-4o on vision-language benchmarks like VQAv2 or COCO-QA?

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