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Diffusion Classifiers Understand Compositionality, but Conditions Apply

arXiv — cs.CV•Tuesday, November 4, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
Recent advancements in diffusion models are reshaping our understanding of visual scenes, a key aspect of human intelligence. While traditional discriminative models have made strides in computer vision, they often fall short in grasping compositionality. However, generative text-to-image diffusion models have shown remarkable capabilities in synthesizing complex scenes, indicating a potential for deeper compositional understanding. This development is significant as it opens new avenues for applying zero-shot diffusion classifiers, enhancing the versatility and effectiveness of these models in various applications.
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