Multimodal generative models are leading a new trend in artificial intelligence, focusing on the integration of visual and textual data to create multifunctional AI systems that perform various tasks, from image generation to understanding and reasoning across different data types. A key challenge is to enhance the capabilities of autoregressive (AR) models so they can generate high-detail images based on textual descriptions. While diffusion models excel in generating high-quality images, AR models lag behind in image quality, resolution flexibility, and multitasking capabilities. Researchers from Shanghai AI Lab and The Chinese University of Hong Kong have introduced Lum

Developed jointly by researchers from the University of Hong Kong and Bytedance, LlamaGen is an image generation method based on the autoregressive model Llama, which has shown the potential to surpass traditional diffusion models in the field of image generation. The open-source release of LlamaGen quickly garnered nearly 900 stars on GitHub, acknowledging this achievement. This result not only proves the competitiveness of autoregressive models in image generation but also brings new vitality