Author

Jongwook Jeon

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#machine learning Preprint Oct 2026

Unbalanced W-Flow: Unbalanced Wasserstein Drifting under Finite-Batch Marginal Fluctuations

Teacher-free one-step generative models such as W-Flow learn directly from distributional objectives, with the Sinkhorn divergence providing the strongest empirical performance among the energies studied in W-Flow. However, Sinkhorn divergence is based on balanced optimal transport, whose exact marginal constraints can...

Jongwook Jeon, Mingue Park, Jiwon Choi et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Learning Multimodal One-step Flow Policy via Value-weighted Optimal Transport

This work introduces One-step Flow policy via Optimal Transport (OptiFlow), a framework for one-step flow policy learning as a structured sample-allocation problem and demonstrates that OptiFlow effectively captures optimal multimodal behaviors and achieves strong performance across diverse offline RL benchmarks.

Jaehun Shon, Jin-Ha Choi, Jongwook Jeon et al. · 0 citations