2 citations · 2 across the 11 of their papers we have counts for
5 papers · 1 filter
DexWeave: Learning Dexterous Humanoid Loco-Manipulation from Human Demonstrations
Naichuan Sun, Haotian Shen, Yizhang Zhang +5
Learning dexterous humanoid loco-manipulation from human demonstrations requires transferring not only human motion, but also the coordinated interaction structure underlying the d…
WorldSimProbe: Diagnosing Simulator Faithfulness in Action-Conditioned World Models for Embodied Manipulation
Peterson Co, Sicheng Hu, Chunxuan Jiao +17
Action-conditioned world models (ACWMs) promise to provide embodied AI with scalable predictive simulators for planning, policy evaluation, and data generation. Realizing this prom…
Beyond Flat Policies: Hierarchical Post-Training for Embodied Agents in Robotic Manipulation
He Kong, Zengjue Chen, Qi Wang +6
Vision-language-action (VLA) models have demonstrated remarkable capabilities in robotic manipulation by leveraging pretrained vision-language models. However, existing post-traini…
FlowHOI: Flow-based Semantics-Grounded Generation of Hand-Object Interactions for Dexterous Robot Manipulation
Huajian Zeng, Lingyun Chen, Jiaqi Yang +4
Recent vision-language-action (VLA) models can generate plausible end-effector motions, yet they often fail in long-horizon, contact-rich tasks because the underlying hand-object i…
VMTS: Vision-Assisted Teacher-Student Reinforcement Learning for Multi-Terrain Locomotion in Bipedal Robots
Fu Chen, Rui Wan, Peidong Liu +2
Bipedal robots, due to their anthropomorphic design, offer substantial potential across various applications, yet their control is hindered by the complexity of their structure. Cu…