WTF?! Simulation-Free Reinforcement Learning with Wasserstein-Tilted Flow Maps
cs.LG, cs.CV, stat.ML
Submitted: 2026-09-22
Updated: 2026-09-22
Terminology
Sources
- Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
- Flow Map Language Models: One-step Language Modeling via Continuous Denoising
- Categorical Flow Maps
- Discrete Flow Maps
- Flow map matching with stochastic interpolants: A mathematical framework for consistency models
- Transition Models: Rethinking the Generative Learning Objective
- Stochastic Interpolants: A Unifying Framework for Flows and Diffusions
- Score-Based Generative Modeling through Stochastic Differential Equations
- Elucidating the Design Space of Diffusion-Based Generative Models
- Optimal transport over a linear dynamical system
- On the relation between optimal transport and Schr\"odinger bridges: A stochastic control viewpoint
- Reinforce Adjoint Matching: Scaling RL Post-Training of Diffusion and Flow-Matching Models
- Flow-GRPO: Training Flow Matching Models via Online RL
- Classifier-Free Diffusion Guidance
- FlowDPS: Flow-Driven Posterior Sampling for Inverse Problems
- Decoupled MeanFlow: Turning Flow Models into Flow Maps for Accelerated Sampling
- Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models
- Gemma 3 Technical Report
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