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Found 2 papers, 1 papers with code
Explaining generative diffusion models via visual analysis for interpretable decision-making process
To address this issue, we propose the three research questions to interpret the diffusion process from the perspective of the visual concepts generated by the model and the region where the model attends in each time step.
NeuroInspect: Interpretable Neuron-based Debugging Framework through Class-conditional Visualizations
We validate the effectiveness of our framework by addressing false correlations and improving inferences for classes with the worst performance in real-world settings.
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