A cross-attention layer allows the model to align parts of the input text with specific regions of the output image. For instance, "a red apple on a blue table" ensures the red apple is distinct and on a blue table. reinforcement learning is sometimes applied to align generated images with user expectations. It can create unique, unseen images like "a giraffe wearing a spacesuit" based on learned patterns.
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