Ambient Discrete Diffusion: Using the Wrong Data at the Right Time for Data Efficient Learning
We introduce RefineMix, a framework for training discrete diffusion models under severe data scarcity, a common constraint in scientific applications. RefineMix uses out-of-distribution data at selected diffusion times to improve generalization without biasing the sampling distribution. Although this strategy has been...