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Arxiv
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185
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DDIL: Diversity Enhancing Diffusion Distillation With Imitation Learning
- Diffusion models excel at generative modeling but have limitations in sampling due to multiple denoising network passes.
- Co-variate shift is identified as a reason for poor performance of multi-step distilled models.
- To address co-variate shift, the researchers propose a diffusion distillation within an imitation learning framework (DDIL).
- DDIL enhances training distribution for distilling diffusion models, improving performance and stability.
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