UniIntervene: Agentic Intervention for Efficient Real-World Reinforcement Learning
DGX agentarXiv:2606.12372v1 Announce Type: cross Abstract: Human-in-the-loop reinforcement learning (HiL-RL) has emerged as an effective paradigm for real-world robotic manipulation, enabling online policy imp