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How do multimodal vision-language models combine images and text, and what role does CLIP play?

For AI / LLM Engineerresearch-engineerML Engineer
The short answer

Vision-language models encode images with a vision encoder and project those features into the language model's token space so it can reason over images and text jointly, often via a connector or projection layer. CLIP is a contrastively trained image-text model that aligns image and text embeddings in a shared space, widely used as the vision backbone or for zero-shot retrieval and grounding.

How to think about it

Vision-language models encode images with a vision encoder and project those features into the language model’s token space so it can reason over images and text jointly, often via a connector or projection layer. CLIP is a contrastively trained image-text model that aligns image and text embeddings in a shared space, widely used as the vision backbone or for zero-shot retrieval and grounding.

Learn it properly Multimodal (vision & audio) LLMs

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