arXiv Computer Vision
The Past Frames the Future: Memory for Autoregressive Video Generation
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arXiv Computer Vision
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Relax Forcing: Relaxed KV-Memory for Consistent Long Video Generation
The paper introduces Relax Forcing, a training‑free memory mechanism for autoregressive video diffusion that structures temporal context into Sink, Tail, and History frames. By selecting History frames with a relaxation criterion, the method reduces error accumulation and attention overhead while preserving motion dynamics. Experiments on VBench‑Long demonstrate that this structured memory improves long‑video generation quality over existing baselines.
arXiv Machine Learning
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Echo-Memory: A Controlled Study of Memory in Action World Models
arXiv:2606. 09803v1 Announce Type: cross Abstract: We present \textbf{Echo-Memory}, a controlled study of memory mechanisms in action-conditioned world models.
arXiv Computer Vision
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LayerRecall: A State-Conditioned Memory Router for Long-Horizon Consistency in Video Generation
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Compress to Remember: Learning Compact Memory via On-Policy Distillation for Long Video Generation
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arXiv Computer Vision
1d ago
APM-Bench: Benchmarking Cross-session Persistent Memory for Egocentric Streaming Video Assistants
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arXiv Computer Vision
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Teaching Video Generators to Remember: Eliciting Dynamic Memory for Out-of-Sight State Evolution
arXiv:2605.25333v3 Announce Type: replace Abstract: Video world models should maintain evolving states when evidence is unobserved, yet current generators often freeze hidden states upon interruption...