Towards High-DoF Dexterous Manipulation through VLA Post-Training
cs.RO
Submitted: 2026-09-17
Updated: 2026-09-17
Terminology
Sources
- LASER: Learning a Latent Action Space for Efficient Reinforcement Learning
- $\pi^{*}_{0.6}$: a VLA That Learns From Experience
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- BORA: Bridging Offline Reinforcement Learning and Online Residual Adaptation for Real-World Dexterous VLA Models
- DexHiL: A Human-in-the-Loop Framework for Vision-Language-Action Model Post-Training in Dexterous Manipulation
- Hand-in-the-Loop: Improving VLA Policies for Dexterous Manipulation via Seamless Hand-Arm Intervention
- Octo: An Open-Source Generalist Robot Policy
- Open X-Embodiment: Robotic Learning Datasets and RT-X Models
- Solving Rubik's Cube with a Robot Hand
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- RL Token: Bootstrapping Online RL with Vision-Language-Action Models
- Beyond Action Residuals: Real-World Robot Policy Steering via Bottleneck Latent Reinforcement Learning
- Dynamic Execution Horizon Prediction for Chunk-based Robot Policies
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