The rapid rise of deep generative models signifies a fundamental shift in AI research and applications, prompting significant questions worthy of exploration. There is a resurgence of interest in integrating Generative Adversarial Networks (GANs) with the DM to achieve rapid and high-fidelity generation. This event seeks to spark interactive discussions focused on improving training and sampling efficiency within the domain of DM and GAN.