5 papers
PFM-HR: Pose Flow Matching for Humanoid Robots
Yukang Gao, Yi Gu, Yangchen Zhou +9
Motion priors improve reinforcement learning for physics-based humanoid tracking, but temporal priors require ordered motion clips, while pose priors provide limited guidance for p…
A Scalable Whole-body Motion Transfer via Implicit Kinodynamic Motion Retargeting
Xingyu Chen, Hanyu Wu, Sikai Wu +7
Human-to-humanoid imitation learning presents a promising pathway to address the severe data scarcity bottleneck in robotics by utilizing abundant, large-scale human motion collect…
SALT: When More Rollouts Don't Help in Group-Based Policy Optimization and How to Make Them Matter
Powei Chang, Jinpeng Zhang, Chaoqun Sun +6
Reinforcement learning with verifiable rewards (RLVR) often adopts GRPO-style group-relative updates, sampling multiple rollouts per prompt to construct normalized learning signals…
SPICE: Submodular Penalized Information-Conflict Selection for Efficient Large Language Model Training
Powei Chang, Jinpeng Zhang, Bowen Chen +9
Information-based data selection for instruction tuning is compelling: maximizing the log-determinant of the Fisher information yields a monotone submodular objective, enabling gre…
PDF-HR: Pose Distance Fields for Humanoid Robots
Yi Gu, Yukang Gao, Yangchen Zhou +7
Pose and motion priors play a crucial role in humanoid robotics. Although such priors have been widely studied in human motion recovery (HMR) domain with a range of models, their a…