Author

Wei-Jun Dong

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Preprint Oct 2026

Sample-Efficient Reinforcement Learning for Policy Improvement via Flow-Reversed Action Anchors

Generalist robot policies offer strong behavioral priors, but achieving deployment-level reliability and throughput remains difficult. Reinforcement learning (RL) can improve these policies, yet its effectiveness is constrained by the cost of online interaction. Existing methods adapt frozen flow-matching policies by t...

Carl Qi, Wei-Jun Dong, Xiao-Jie Wang et al. · 0 citations

Preprint Oct 2026

Residual Modeling Closes the Regression and Generative Policy Gap in Robot Learning

Heteroscedastic Student-t action regression (HT-Policies) is introduced, which learns input-dependent residual scales and reduces the influence of heavy tails and offers an efficient direct-regression alternative for a range of architectures and tasks.

Yu-Chen Zhou, Jia-Cheng You, Wei-Kang Wan et al. · 0 citations