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Ring Forcing: Towards Precise Long-Term Memory for Autoregressive Video Diffusion

arXiv · AI, language, vision and robotics · article · Aug 27, 2026 · UTC

Scaling video generation to long durations reveals a critical bottleneck: current models lack robust long-term memory. This deficiency can be studied along two critical aspects: object permanence, the ability to precisely reproduce the appearance of objects upon re-entry; and memory capacity, the ability to process ultra-long context and use information from distant history. Robust long-term memory requires both: object permanence without sufficient context handling limits the temporal scope, while long context length without permanence fails to maintain identity. To address this, we present R

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