Understanding, Accelerating, and Improving MeanFlow Training
📰 ArXiv cs.AI
Learn to accelerate and improve MeanFlow training by understanding its dynamics and velocity fields
Action Steps
- Analyze the interaction between instantaneous and average velocity fields in MeanFlow training
- Apply the findings to adjust the training dynamics and improve the learning of instantaneous velocity
- Use the average velocity to benefit the learning of instantaneous velocity when the temporal gap is small
- Implement techniques to accelerate MeanFlow training based on the understanding of its dynamics
- Evaluate the performance of the improved MeanFlow model using relevant metrics
Who Needs to Know This
Researchers and engineers working on generative modeling and MeanFlow training can benefit from this knowledge to improve their models' performance and efficiency
Key Insight
💡 Well-established instantaneous velocity is a prerequisite for learning average velocity in MeanFlow training
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🚀 Accelerate and improve MeanFlow training by understanding its dynamics and velocity fields! 🤖
Full Article
Title: Understanding, Accelerating, and Improving MeanFlow Training
Abstract:
arXiv:2511.19065v2 Announce Type: replace-cross Abstract: MeanFlow promises high-quality generative modeling in few steps, by jointly learning instantaneous and average velocity fields. Yet, the underlying training dynamics remain unclear. We analyze the interaction between the two velocities and find: (i) well-established instantaneous velocity is a prerequisite for learning average velocity; (ii) learning of instantaneous velocity benefits from average velocity when the temporal gap is small,
Abstract:
arXiv:2511.19065v2 Announce Type: replace-cross Abstract: MeanFlow promises high-quality generative modeling in few steps, by jointly learning instantaneous and average velocity fields. Yet, the underlying training dynamics remain unclear. We analyze the interaction between the two velocities and find: (i) well-established instantaneous velocity is a prerequisite for learning average velocity; (ii) learning of instantaneous velocity benefits from average velocity when the temporal gap is small,
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