GROVE: A Generalized Reward for Learning Open-Vocabulary Physical Skill
Jieming Cui, Tengyu Liu, Ziyu Meng, Jiale Yu, Ran Song, Wei Zhang, Yixin Zhu, Siyuan Huang
2025Year
4Top-tier citations
Abstract
GROVE Figure 1 . Open-vocabulary physical skills learned with our generalized reward framework GROVE. The white humanoid mannequins demonstrate diverse skills from abstract instructions (e.g., "conduct the orchestra," "position body in a shape of C") using a pre-trained controller. The system also generalizes to standard RL benchmarks, including the Ant, Humanoid, and quadrupedal ANYmal, all without task-specific reward engineering.
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Cited by top-tier papers4
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Builds on18
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- AMASS: Archive of Motion Capture As Surface ShapesNaureen Mahmood, Nima Ghorbani, Nikolaus F. Troje, Gerard Pons-Moll et al.ICCV 2019 · 1,784 citations
- MotionGPT: Human Motion as a Foreign LanguageBiao Jiang, Xin Chen, Wen Liu, Jingyi Yu et al.NeurIPS 2023 · 698 citations
- Eureka: Human-Level Reward Design via Coding Large Language ModelsYecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang et al.ICLR 2024 · 582 citations
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