UniDexTok learns embodiment-conditioned discrete tokens from a 22-DoF unified semantic interface to enable retargeting-free, cross-embodiment state representation for heterogeneous dexterous hands using real data.
Gr-dexter technical report
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
fields
cs.RO 4years
2026 4representative citing papers
DexJoCo is a benchmark and toolkit with 11 functionally grounded tasks, 1.1K trajectories, and empirical benchmarks for task-oriented dexterous manipulation on MuJoCo.
HandITL enables seamless human intervention in VLA policies for bimanual dexterous manipulation, cutting jitter by 99.8% and improving refined policies by 19% over standard teleoperation.
ConTrack introduces a constrained RL method with online dual-variable adaptation and adaptive resets for improved long-horizon hand tracking in simulation and on real robots.
citing papers explorer
-
UniDexTok: A Unified Dexterous Hand Tokenizer from Real Data
UniDexTok learns embodiment-conditioned discrete tokens from a 22-DoF unified semantic interface to enable retargeting-free, cross-embodiment state representation for heterogeneous dexterous hands using real data.
-
Hand-in-the-Loop: Improving VLA Policies for Dexterous Manipulation via Seamless Hand-Arm Intervention
HandITL enables seamless human intervention in VLA policies for bimanual dexterous manipulation, cutting jitter by 99.8% and improving refined policies by 19% over standard teleoperation.
-
ConTrack: Constrained Hand Motion Tracking with Adaptive Trade-off Control
ConTrack introduces a constrained RL method with online dual-variable adaptation and adaptive resets for improved long-horizon hand tracking in simulation and on real robots.