BitDance: Scaling Autoregressive Generative Models with Binary Tokens скачать в хорошем качестве

BitDance: Scaling Autoregressive Generative Models with Binary Tokens

BitDance is a novel autoregressive framework for image generation that addresses the trade-off between image fidelity and computational efficiency by utilizing high-entropy binary visual tokens. To manage the complexity of sampling from the resulting massive vocabulary space, the model introduces a binary diffusion head that models discrete tokens as vertices within a continuous hypercube, thereby avoiding the parameter explosion associated with traditional classification methods. This architecture enables a "next-patch" diffusion strategy, allowing the model to predict multiple tokens in parallel to significantly accelerate inference while preserving the structural dependencies required for high-quality images. Consequently, BitDance achieves state-of-the-art performance on benchmarks like ImageNet and demonstrates superior speed and efficiency compared to existing large-scale autoregressive models. https://arxiv.org/pdf/2602.14041 https://github.com/shallowdream204/Bi... https://bitdance.csuhan.com/