metadata
license: mit
base_model:
- Wan-AI/Wan2.1-T2V-1.3B
pipeline_tag: text-to-video
HiAR
Hierarchical Autoregressive Video Generation with Pipelined Parallel Inference
arXiv | Website | Code | Model
HiAR proposes hierarchical denoising for autoregressive video diffusion models, a paradigm shift from conventional block-first to step-first denoising order. By conditioning each block on context at a matched noise level, HiAR maximally attenuates error propagation while preserving temporal causality, achieving state-of-the-art long video generation (20s+) with significantly reduced quality drift.