#manipulation
11 notes
- MEM: Multi-Scale Embodied Memory for Vision Language Action Models
- $\pi_{0.5}$: A Vision-Language-Action Model with Open-World Generalization
- $\pi_{0.6}$: A VLA That Learns From Experience
- $\pi$0.7: A Steerable Generalist Robotic Foundation Model with Emergent Capabilities
- Diffusion-VLA: Scaling Robot Foundation Models via Unified Diffusion and Autoregression
- TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policiy
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- GHIL-Glue: Hierarchical Control with Filtered Subgoal Images
- Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning
- Generalizable Humanoid Manipulation with Improved 3D Diffusion Policies
- What is Manipulation?