3 papers
cs.RO2026
Think Only When Needed: Prompt-Authority Control for Selective Slow-Path Intervention in Vision-Language-Action Manipulation
Zhiruo Zhou, Zelin Li, Xiwen Chen +4
Retrieval can efficiently and effectively augment a frozen vision--language--action (VLA) policy without retraining, yet retrieved text becomes a control intervention once it enter…
cs.RO2026
Pointing-VLA: Typed Spatial Grounding Interfaces for Vision-Language-Action Manipulation
Xiwen Chen, Zelin Li, Zhiruo Zhou +3
Vision-language-action (VLA) models often expose spatial grounding through autoregressive text coordinates or opaque action tokens, creating brittle interfaces between multimodal r…
cs.RO2026
Rethinking Demonstration Unlearning in Imitation Learning for Robotics
Jiazhuo Li, Yu Zhang, Yiming Fei +4
Imitation learning for robotics depends on human demonstrations, some of which people may later ask to remove. Retraining without them is the natural reference, but its cost grows…