Author

Yeonwoo Cha

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#artificial intelligence Apr 2026

Training-Free Refinement of Flow Matching with Divergence-based Sampling

The Flow Divergence Sampler is proposed, a training-free framework that refines intermediate states before each solver step that consistently improves fidelity across various generation tasks including text-to-image synthesis, and inverse problems.

Yeonwoo Cha, Jaehoon Yoo, Semin Kim et al. · arXiv.org · 4 citations