AI RESEARCH
Q-ARVD: Quantizing Autoregressive Video Diffusion Models
arXiv CS.CV
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ArXi:2605.21072v1 Announce Type: new Autoregressive video diffusion models (ARVDs) have emerged as a promising architecture for streaming video generation, paving the way for real-time interactive video generation and world modeling. Despite their potential, the substantial inference cost of ARVDs remains a major obstacle to practical deployment, making model quantization a natural direction for improving efficiency. However, quantization for ARVDs remains largely unexplored.