DiT-MoE: A New Version of the DiT Architecture for Image Generation

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Researchers from Kunlun Inc. have introduced DiT-MoE, an advanced version of the DiT architecture for image generation, that incorporates sparse Mixture of Experts (MoE) layers to enhance efficiency and performance. This new model significantly outperforms previous architectures in conditional image generation tasks, using fewer parameters and achieving lower Frechet Inception Distance (FID) scores. The study highlights the potential of sparse conditional computation in diffusion models and proposes future improvements in expert architectures and knowledge distillation.