2 papers
cs.LG2026
WTF?! Simulation-Free Reinforcement Learning with Wasserstein-Tilted Flow Maps
Abbas Mammadov, Jerry Y. Huang, Justin Lin +5
Reward fine-tuning aims to update a pre-trained flow-based generative model to improve the downstream reward of its generated samples. Existing methods typically formulate this pro…
cs.LG2026
How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance
Jerry Y. Huang, Justin Lin, Sheel Shah +2
In generative modeling, we often wish to produce samples that maximize a user-specified reward such as aesthetic quality or alignment with human preferences, a problem known as \te…