arXiv Machine Learning June 26, 2026 By Mingyang Lyu, Yinqian Sun, Erliang Lin, Huangrui Li, Ruolin Chen, Feifei Zhao, Yi Zeng

Reinforcement Fine-Tuning of Flow-Matching Policies for Vision-Language-Action Models

Read the original on arXiv Machine Learning →

arXiv:2510. 09976v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models such as OpenVLA, Octo, and $\pi_0$ have shown strong generalization by leveraging large-scale demonstrations, yet their performance is still fundamentally constrained by the quality and coverage of supervised data.

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

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