Cloak: Zero-Shot Cross-Embodiment Manipulation by Masking the End-Effector from the VLA

arXiv:2606.22836 · cs.RO · Submitted 2026-06-22 · Read on arXiv

cs.RO

Submitted: 2026-06-22

Updated: 2026-09-25

Code: https://github.com/kevinzakka/mink

Terminology

• Zero-Shot Transfer — 9× in this paper · explained in 4 episodes
• Cross-Embodiment Transfer — 8× in this paper · explained in 2 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Calibration — 6× in this paper · explained in 7 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Generative Model — 5× in this paper · explained in 2 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• In Conference on Robot Learning — 4× in this paper
• Decoupling — 3× in this paper · explained in 2 episodes
• Hallucination — 3× in this paper · explained in 4 episodes
• Action Space — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• IEEE International Conference on Robotics and Automation — 2× in this paper
• Action Flow — 1× in this paper · explained in 1 episode
• Continual Learning — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Segmentation Masks — 1× in this paper · explained in 2 episodes
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes

Sources

• Open X-Embodiment: Robotic Learning Datasets and RT-X Models
• OpenVLA: An Open-Source Vision-Language-Action Model
• $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
• X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model
• Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation
• RDT2: Exploring the Scaling Limit of UMI Data Towards Zero-Shot Cross-Embodiment Generalization
• LAP: Language-Action Pre-Training Enables Zero-shot Cross-Embodiment Transfer
• EmbodiSwap for Zero-Shot Robot Imitation Learning
• OXE-AugE: A Large-Scale Robot Augmentation of OXE for Scaling Cross-Embodiment Policy Learning
• Augmented Reality for RObots (ARRO): Pointing Visuomotor Policies Towards Visual Robustness
• One Hand to Rule Them All: Canonical Representations for Unified Dexterous Manipulation
• One-Policy-Fits-All: Geometry-Aware Action Latents for Cross-Embodiment Manipulation

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