Parametric Trajectory Distillation for Few-Step Video Generation

arXiv:2610.11498 · cs.CV · Submitted 2026-10-08 · Read on arXiv

cs.CV

Submitted: 2026-10-08

Updated: 2026-10-08

Terminology

• Distillation — 60× in this paper · explained in 2 episodes
• Consistency — 23× in this paper · explained in 3 episodes
• In International Conference on Learning Representations — 11× in this paper
• Adam — 9× in this paper · explained in 2 episodes
• Distribution Matching — 9× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 8× in this paper
• Diffusion Model — 8× in this paper · explained in 8 episodes
• Diffusion Models — 7× in this paper · explained in 6 episodes
• Parametric Trajectory Distillation — 7× in this paper
• Benchmark — 6× in this paper · explained in 2 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Distribution Matching Distillation — 4× in this paper
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• Alignment — 3× in this paper · explained in 1 episode
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Modeling — 3× in this paper · explained in 3 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• International Conference on Machine Learning — 3× in this paper
• LoRA Adapters — 3× in this paper · explained in 3 episodes
• Self-distillation — 3× in this paper · explained in 6 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Parallel Decoding Distillation — 2× in this paper
• Rectified Flow — 2× in this paper · explained in 3 episodes
• Self-consistency — 2× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 7 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• LoRA Fine-Tuning — 1× in this paper · explained in 3 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes

Sources

• V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
• How to build a consistency model: Learning flow maps via self-distillation
• pi-Flow: Policy-Based Few-Step Generation via Imitation Distillation
• GENIE: Higher-Order Denoising Diffusion Solvers
• Phased DMD: Few-step Distribution Matching Distillation via Score Matching within Subintervals
• Bezier Distillation
• AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation
• SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modeling
• WorldJen: An End-to-End Multi-Dimensional Benchmark for Generative Video Models
• B'ezierFlow: Learning B'ezier Stochastic Interpolant Schedulers for Few-Step Generation
• Movie Gen: A Cast of Media Foundation Models
• Align Your Flow: Scaling Continuous-Time Flow Map Distillation
• Wan: Open and Advanced Large-Scale Video Generative Models
• ViMix-14M: A Curated Multi-Source Video-Text Dataset with Long-Form, High-Quality Captions and Crawl-Free Access
• VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness
• Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency

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