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cs.RO2026
Ask-to-Clarify: Resolving Instruction Ambiguity through Multi-turn Dialogue
Xingyao Lin, Xinghao Zhu, Tianyi Lu +6
Embodied agents are intelligent systems designed to perceive, reason, and act within the physical world. While the robotics community has long strived to build such versatile agent…
cs.RO2026
ThinkingVLA: Interleaved Vision and Language Reasoning for Robotic Manipulation
Tianyi Lu, Hui Zhang, Zijie Diao +8
Most Vision-Language-Action (VLA) models map observations directly to actions without explicit reasoning, limiting their capacity for reasoning-intensive long-horizon tasks. To add…
cs.RO2026
ActiveMimic: Egocentric Video Pretraining with Active Perception
Xingyao Lin, Guojin Zhong, Tianyi Lu +4
Egocentric human video offers a scalable alternative to robot data for pretraining, yet models pretrained on such video consistently underperform those pretrained on robot data. We…