Rethinking visual prompting for multimodal large language models with external knowledge
In recent years, multimodal large language models (MLLMs) have made significant strides by training on vast high-quality image-text datasets, enabling them to generally understand images well. However, the inherent difficulty in explicitly conveying fine-grained or spatially dense information in tex...
| Main Authors: | , , , , , , |
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| Format: | Internet publication |
| Language: | English |
| Published: |
2024
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