No retraining needed for any-order image generation: one position table and an ordering curriculum unlock inpainting from old weights
A pretrained raster-scan autoregressive image model can only generate left to right and top to bottom, so it cannot inpaint or outpaint at inference. A new adaptation adds a future-aware positional embedding table and continues training under a curriculum that shifts from raster order to random order, letting the same weights condition on any ordering. On ImageNet, LlamaGen-XL moves from FID 2.63 to 3.91 but gains inpainting and outpainting while keeping KV caching and vLLM serving.