
The dominance of end-to-end learning has fundamentally reshaped how researchers approach computer vision and natural language processing, yet generative models have long stood as a notable exception to this streamlined ideal. Since the breakthrough of AlexNet in 2012, classification models have been able to produce a final decision in a single forward pass, but today’s systems like GPT-4 and Stable










