MORPHOS: Autoregressive 4D Generation with Temporal Structured Latents
Two new research papers explore advancements in autoregressive generation for visual and 4D assets. The first paper, "Where to Refine, When to Stop," introduces a training-free framework called LD-Pruning to significantly reduce inference latency in visual autoregressive models by identifying and removing redundant computations. The second paper, "MORPHOS," presents a novel autoregressive framework for generating dynamic 3D assets from videos, supporting multiple representations and improving temporal consistency. AI
IMPACT These papers introduce novel techniques for improving the efficiency and capabilities of autoregressive generative models in visual and 4D content creation.