Set Diffusion: Interpolating Token Orderings Between Autoregression and Diffusion for Fast and Flexible Decoding

Researchers have introduced Set Diffusion, a framework that combines autoregressive and diffusion-based generation techniques to improve token sequence processing. By bridging the gap between these two architectures, the method enables the use of key-value caching in diffusion models while maintaining the flexibility to generate sequences of varying lengths.