Abstract: Systems and methods for training and using a prompt token generator to generate a set of prompt tokens which, when fed into a pretrained generative image transformer (e.g., an autoregressive transformer, continuous diffusion model, non-autoregressive transformer, or discrete diffusion model), may bias the generative image transformer's output towards a particular domain (e.g., towards a particular class of images, towards a particular training instance, etc.). In some examples, the prompt token generator may be used to generate a set of different prompt token sequences, which may then be fed sequentially to a pretrained non-autoregressive generative image transformer as it iteratively generates each image in each time-step in order to introduce more diversity into the transformer's final output.