Taming Outlier Tokens in Diffusion Transformers

Apple researchers have identified that Diffusion Transformers generate outlier tokens with exceptionally high numerical values that can interfere with image generation stability. By applying specific quantization techniques to these tokens, the team demonstrated that they can compress these models more efficiently without sacrificing visual quality. This finding provides a method to reduce the hardware requirements for running sophisticated generative image models on consumer devices.