Generative Task

Generative tasks focus on creating new data instances, such as images, text, or 3D shapes, that resemble a training dataset. Current research emphasizes improving the efficiency and controllability of generative models, exploring architectures like diffusion models, autoregressive models, and graph neural networks, as well as techniques like prompt engineering and model quantization. These advancements are significant because they enhance the quality, speed, and resource efficiency of generative processes, impacting diverse fields from image synthesis and natural language processing to drug discovery and material design.