Unverified50% confidenceFactExact time
CLIP adopts a dual-tower architecture, consisting of a pretrained visual encoder (such as ViT) and a pretrained text encoder.
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Long-term
Relevance
9/7/2026
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UnverifiedCLIP contains two parallel encoders: the text encoder uses a Transformer-based architecture (a 12-layer Transformer similar to GPT-2), and the visual encoder has two variants—one based on ResNet and one based on ViT.76% similarUnverifiedCLIP has been widely adopted as the standard visual encoder by mainstream multimodal models including LLaVA and InstructBLIP70% similarUnverifiedImage generation models typically use CLIP or similar cross-modal encoders to map text into high-dimensional vectors, which are then used by U-Net or DiT architectures to progressively denoise and generate images in latent space70% similarUnverifiedCurrent mainstream multimodal LLMs convert images into token sequences via a visual encoder (typically CLIP or ViT series) and then align them with the text space through a linear projection layer or cross-attention mechanism.69% similarVerifiedCLIP was released by OpenAI in 2021, simultaneously training an image encoder and a text encoder through contrastive learning to achieve zero-shot image classification.69% similar
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