Recency Forcing: Bridging the Long-Horizon Gap in Autoregressive Video Generation

arXiv:2609.19729 · cs.CV · Submitted 2026-09-17 · Read on arXiv

cs.CV

Submitted: 2026-09-17

Updated: 2026-09-17

Terminology

• Consistency — 17× in this paper · explained in 3 episodes
• Diffusion Model — 12× in this paper · explained in 8 episodes
• Diffusion Models — 11× in this paper · explained in 6 episodes
• Temporal Response Bias — 8× in this paper
• Transformer — 8× in this paper · explained in 2 episodes
• Biased Attention Reparameterization — 7× in this paper
• Ablation — 5× in this paper · explained in 1 episode
• Generative Model — 5× in this paper · explained in 2 episodes
• Distillation — 4× in this paper · explained in 2 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 3× in this paper
• Fidelity — 3× in this paper · explained in 2 episodes
• Flow Matching — 3× in this paper · explained in 7 episodes
• Foundation Model — 3× in this paper · explained in 3 episodes
• KV cache — 3× in this paper · explained in 3 episodes
• Pruning — 3× in this paper · explained in 4 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Distribution Matching — 2× in this paper · explained in 2 episodes
• World Model — 2× in this paper · explained in 7 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Exposure Bias — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Normalizing Flow — 1× in this paper · explained in 3 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Cosmos World Foundation Model Platform for Physical AI
• MAGI-1: Autoregressive Video Generation at Scale
• Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
• SkyReels-V2: Infinite-length Film Generative Model
• Past- and Future-Informed KV Cache Policy with Salience Estimation in Autoregressive Video Diffusion
• Self-Forcing++: Towards Minute-Scale High-Quality Video Generation
• LoL: Longer than Longer, Scaling Video Generation to Hour
• FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
• Autoregressive Video Generation without Vector Quantization
• Flex Attention: A Programming Model for Generating Optimized Attention Kernels
• End-to-End Training for Autoregressive Video Diffusion via Self-Resampling
• AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
• LTX-Video: Realtime Video Latent Diffusion
• RELIC: Interactive Video World Model with Long-Horizon Memory
• Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion
• FIFO-Diffusion: Generating Infinite Videos from Text without Training
• HunyuanVideo: A Systematic Framework For Large Video Generative Models
• Rolling Sink: Bridging Limited-Horizon Training and Open-Ended Testing in Autoregressive Video Diffusion
• Train Short, Inference Long: Training-free Horizon Extension for Autoregressive Video Generation
• Unified Video Action Model

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