arXiv Machine Learning July 17, 2026 By Zikun Zhang, Jiayuan Sheng, David D. Yao, Wenpin Tang

A Continuous-Time Reinforcement Learning Framework for Fine-Tuning Discrete Diffusion Models

Read the original on arXiv Machine Learning →

arXiv:2607. 14522v1 Announce Type: new Abstract: We formulate reinforcement learning (RL) in continuous time with discrete state spaces and possibly arbitrary action spaces via a stochastic control approach, where the state dynamics are modeled as a controlled continuous-time Markov chain (CTMC).

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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