Accelerating Flow-based Models: Joint Distillation for Efficient Inference
Published:Dec 2, 2025 10:48
•1 min read
•ArXiv
Analysis
This ArXiv paper explores improvements in the efficiency of flow-based models, which are known for their strong generative capabilities. The focus on joint distillation suggests a novel approach to address computational bottlenecks in likelihood evaluation and sampling.
Key Takeaways
Reference
“The paper focuses on fast likelihood evaluation and sampling in flow-based models.”