Google Research explains where diffusion-model creativity comes from: score smoothing enables interpolation
Towards demystifying the creativity of diffusion models
What happened
In a paper at ICLR 2026, Google Research explains that diffusion-model creativity comes from score smoothing during neural-network training. Regularization makes the learned score function smooth, so denoising interpolates between training data points and generates new samples.
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