Large Scale Generative Model

Large-scale generative models are revolutionizing various fields by creating high-quality, realistic data across diverse modalities, including images, videos, and 3D models. Current research focuses on improving model scalability, controllability (e.g., through multi-conditional inputs and self-guidance), and evaluation methods (including reference-free approaches), often employing diffusion models, GANs, and transformers. These advancements are significantly impacting scientific discovery (e.g., in neuroscience and astronomy) and practical applications, such as medical image synthesis, robotics, and digital content creation, while also raising important considerations regarding trustworthiness and potential biases.