7 citations · 17 across the 7 of their papers we have counts for
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cs.RO2026
PreferenceFlow: Test-Time Guidance of Flow-Matching Robot Policies from Human Interventions
Yiqi Tang, Diyuan Shi, Runze Li +1
Flow-matching policies can represent complex robot behaviors but remain susceptible to local errors under distribution shift at deployment. Many reinforcement learning approaches t…
cs.RO2026
World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems
Runze Li, Hongyin Zhang, Junxi Jin +5
Vision-Language-Action (VLA) models have emerged as a promising paradigm for building embodied agents that ground perception and language into action. However, most existing approa…
cs.RO2026
NFPO: Stabilized Policy Optimization of Normalizing Flow for Robotic Policy Learning
Diyuan Shi, Yiqi Tang, Zifeng Zhuang +1
Deep Reinforcement Learning (DRL) has experienced significant advancements in recent years and has been widely used in many fields. In DRL-based robotic policy learning, however, c…