Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logits

ArXi:2602.15405v2 Announce Type: replace Robust classification in noisy environments remains a fundamental challenge in machine learning. Standard approaches typically treat signal enhancement and classification as separate, sequential stages: first enhancing the signal and then applying a classifier. This approach fails to leverage the semantic information in the classifier's output during denoising.