Diffusion versus Auto-regressive models for image generation. Which is better? [D] [R]

Hello all,

I am new to this field of image generation using transformer models. I am curious about the above two mentioned approaches. Particularly in light of this paper "[Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction](https://arxiv.org/abs/2404.02905)" ([results](https://github.com/FoundationVision/VAR?tab=readme-ov-file#-for-the-first-time-gpt-style-autoregressive-models-surpass-diffusion-models)). It looks like these AR (auto-regressive) models seem to be better especially when scaled up compared to DiTs (Diffusion Transformers). Their main inference benefits seem to come from the low sampling efficiency of DiT.

However, I have my doubts regarding this. …

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