AI RESEARCH
A$^2$RD: Agentic Autoregressive Diffusion for Long Video Consistency
arXiv CS.AI
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ArXi:2605.06924v1 Announce Type: cross Synthesizing consistent and coherent long video remains a fundamental challenge. Existing methods suffer from semantic drift and narrative collapse over long horizons. We present A$^2$RD, an Agentic Auto-Regressive Diffusion architecture that decouples creative synthesis from consistency enforcement. A$^2$RD formulates long video synthesis as a closed-loop process that synthesizes and self-improves video segment-by-segment through a Retrieve--Synthesize--Refine--Update cycle.