Score-Regularized Joint Sampling with Importance Weights for Flow Matching

Researchers propose a new non-IID sampling framework for flow matching models that improves estimation accuracy by jointly drawing diverse samples and using score-based regularization. The method includes importance weighting techniques to enable unbiased estimation while maintaining sample quality and diversity.