Show-o and Discrete-Diffusion Unified Models

Transfusion mixes continuous and discrete representations. Show-o (Xie et al., August 2024) goes the other way: text tokens use causal next-token prediction, image tokens use masked discrete diffusion in the spirit of MaskGIT. Both sit inside one transformer with a hybrid attention mask. The result unifies VQA, text-to-image, inpainting, and mixed-modality generation on one backbone, one tokenizer per modality, one loss formulation (next-token extended to masked prediction). This lesson walks the Show-o design — why masked discrete diffusion is a parallel, few-step image generator — and contrasts with Transfusion and Emu3.