Refinement-Based Flow Policy Optimization

arXiv:2609.15123 · cs.LG, cs.AI · Submitted 2026-09-14 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-09-14

Updated: 2026-09-27

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Flow Matching — 16× in this paper · explained in 8 episodes
• Reinforcement Learning — 14× in this paper · explained in 4 episodes
• Adaptation — 9× in this paper · explained in 1 episode
• Actor — 8× in this paper · explained in 3 episodes
• Online Reinforcement Learning — 8× in this paper · explained in 2 episodes
• Action Space — 5× in this paper · explained in 1 episode
• Refinement-Based Flow Policy Optimization — 4× in this paper
• Adam — 3× in this paper · explained in 2 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• EMMA — 2× in this paper · explained in 2 episodes
• Generative Modeling — 2× in this paper · explained in 3 episodes
• Mode Collapse — 2× in this paper · explained in 2 episodes
• Alternation — 1× in this paper · explained in 1 episode
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Korea Advanced Institute of Science and Technology — 1× in this paper
• Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Learning to Draw Samples with Amortized Stein Variational Gradient Descent
• Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review
• Approximate Inference with Amortised MCMC
• Policy Representation via Diffusion Probability Model for Reinforcement Learning
• Real-Time Generative Policy via Langevin-Guided Flow Matching for Autonomous Driving

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