Learning to Act under Visual Interruptions with Vision-Language-Action Models
cs.RO, cs.AI
Submitted: 2026-09-28
Updated: 2026-09-28
Code: https://github.com/NVIDIA/Isaac-GR00T
Project page: https://minglejiang.github.io/Mail-Bench
Terminology
Sources
- Persistent Robot World Models: Stabilizing Multi-Step Rollouts via Reinforcement Learning
- RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
- Ctrl-World: A Controllable Generative World Model for Robot Manipulation
- Reinforcement Learning-Guided Retrieval with Soft Fusion for Robust Multimodal Imitation Learning under Missing Modalities
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- When Sensors Fail: Temporal Sequence Models for Robust PPO under Sensor Drift
- StellaVLA: In-Context Structured Demonstration for Generalizable Vision-Language-Action Models
- Do World Action Models Generalize Better than VLAs? A Robustness Study
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