Improving Cross-embodiment Transfer in Latent Action Models with Action-Similarity Supervision

arXiv:2609.19846 · cs.RO, cs.AI · Submitted 2026-09-17 · Read on arXiv

cs.RO, cs.AI

Submitted: 2026-09-17

Updated: 2026-09-17

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Action Space — 18× in this paper · explained in 1 episode
• Cross-Embodiment Transfer — 9× in this paper · explained in 2 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Benchmark — 6× in this paper · explained in 2 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Transformer — 4× in this paper · explained in 2 episodes
• World Model — 4× in this paper · explained in 7 episodes
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Decode — 2× in this paper · explained in 2 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• International Conference on Machine Learning — 2× in this paper
• Latent Representation — 2× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Action Flow — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Closed-Loop Control — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• VLA Models — 1× in this paper · explained in 3 episodes
• Variational Auto Encoder — 1× in this paper
• Vision-Language-Action (VLA) Models — 1× in this paper · explained in 2 episodes
• Vision-language models — 1× in this paper · explained in 2 episodes

Sources

• Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models
• DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
• MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations
• Moto: Latent Motion Token as the Bridging Language for Learning Robot Manipulation from Videos
• What Makes Video World Model Latents Action-Relevant: Prediction over Reconstruction
• Latent Action Learning Requires Supervision in the Presence of Distractors
• RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
• OpenVLA: An Open-Source Vision-Language-Action Model
• ConLA: Contrastive Latent Action Learning from Human Videos for Robotic Manipulation
• MVP-LAM: Learning Action-Centric Latent Action via Cross-Viewpoint Reconstruction
• villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models
• UniVLA: Learning to Act Anywhere with Task-centric Latent Actions
• X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model
• Emergence of Human to Robot Transfer in Vision-Language-Action Models

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