What is the impact of multimodal observation diversity (e.g., vision+text vs. vision+audio vs. vision+tactile)

Abstract

Abstract: Abstract With the urgent demand for generalized deep models, many pre-trained big models are proposed, such as bidirectional encoder representations (BERT), vision transformer (ViT), generative pre-trained transformers (GPT), etc. Inspired by the success of these models in single domains (like computer vision and natural language processing), the multi-modal pre-trained big models have also drawn more and more attention in recent years. In this work, we give a comprehensive survey of these models and hope this paper could provide new insights and helps fresh researchers to track the most cutti

Research Question

What is the impact of multimodal observation diversity (e.g., vision+text vs. vision+audio vs. vision+tactile) on the zero-shot generalization performance of transformer-based models, measured by accuracy on cross-modal retrieval benchmarks like COCO-Text and AVS?

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