Simple-to-Complex Structured Demonstrations for Vision-Language-Action Learning
Vision-Language-Action (VLA) models have demonstrated strong capabilities in robotic manipulation by integrating visual perception, language understanding, and robot action generation. Existing research has primarily focused on improving model architectures, training strategies, and dataset scale, while little attention has been paid to how demonstrations are collected and organized. We identify demonstration organization as a fundamental yet overlooked aspect of imitation learning, as it directly affects policy learning efficiency, training stability, and policy generalization. To address thi
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- PossiblePossibly related (embedding) · 54%vlm-starter →
- PossiblePossibly related (embedding) · 54%lucidrains/mimic-video →
- FuzzySimilar title/name (fuzzy) · 59%VioletVision-3B →
“Fuzzy title match (0.73): “Simple-to-Complex Structured Demonstrations for Vision-Langu” ≈ “VioletVision-3B””
- LinkedLinked via arxiv author · 85%Xinchuan Qiu →
“Simple-to-Complex Structured Demonstrations for Vision-Language-Action Learning”
- LinkedLinked via arxiv author · 85%Yi Yu →
“Simple-to-Complex Structured Demonstrations for Vision-Language-Action Learning”
- PossiblePossibly related (embedding) · 49%UK startup Humanoid launches reinforcement learning system to improve robot manipulation - Robotics & Automation News →
- FuzzySimilar title/name (fuzzy) · 84%pytorch/vision →
“Fuzzy title match (0.92): “Simple-to-Complex Structured Demonstrations for Vision-Langu” ≈ “pytorch/vision””
- FuzzySimilar title/name (fuzzy) · 59%aymericdamien/TopDeepLearning →
“Fuzzy title match (0.73): “Simple-to-Complex Structured Demonstrations for Vision-Langu” ≈ “aymericdamien/TopDeepLearning””