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Does it beat them because it's a transformer, or because it's a much larger end-to-end model with higher quality multimodal training?

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I wonder if it benefits because it can attend to individual tokens of the prompt while generating, compared to typical diffusion models that just get a static vector embedding of the prompt.

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