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cs.RO2025
Universal Dexterous Functional Grasping via Demonstration-Editing Reinforcement Learning
Chuan Mao, Haoqi Yuan, Ziye Huang +3
Reinforcement learning (RL) has achieved great success in dexterous grasping, significantly improving grasp performance and generalization from simulation to the real world. Howeve…
cs.LG2025★ 4 cited
Agentic Reinforced Policy Optimization
Guanting Dong, Hangyu Mao, Kai Ma +11
Large-scale reinforcement learning with verifiable rewards (RLVR) has demonstrated its effectiveness in harnessing the potential of large language models (LLMs) for single-turn rea…