MaskVLA: Visual Masking Against Trajectory Overfitting of Vision-Language-Action Model

arXiv:2609.23565 · cs.CV, cs.AI, cs.RO · Submitted 2026-09-20 · Read on arXiv

cs.CV, cs.AI, cs.RO

Submitted: 2026-09-20

Updated: 2026-09-20

Comments: 8 pages, 7 figures. Accepted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026)

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

Terminology

• Generalization — 22× in this paper · explained in 13 episodes
• Fine-Tuning — 17× in this paper · explained in 5 episodes
• Representation Learning — 5× in this paper · explained in 2 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• VLA Models — 5× in this paper · explained in 3 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Data Augmentation — 4× in this paper · explained in 7 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Foundation Model — 3× in this paper · explained in 3 episodes
• Vision-Language-Action (VLA) Models — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Diffusion Policy — 2× in this paper
• Interpretability — 2× in this paper · explained in 15 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Cooperation — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Diffusion Policy (DP) — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• IEEE International Conference on Robotics and Automation — 1× in this paper
• Latent Space — 1× in this paper · explained in 7 episodes
• Multimodal Inputs — 1× in this paper · explained in 2 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes
• Vision-language models — 1× in this paper · explained in 2 episodes

Sources

• RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
• UniVLA: Learning to Act Anywhere with Task-centric Latent Actions
• GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
• SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model
• DINOv2: Learning Robust Visual Features without Supervision
• Shortcut Learning in Generalist Robot Policies: The Role of Dataset Diversity and Fragmentation

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