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cs.RO2026
World-Calibrated Proposal-to-Action Flow for Vision-Language-Action Models
Jie He, Wei Li, Junwen Tong +3
Flow-based Vision-Language-Action (VLA) policies generate action chunks by transporting samples from a task-agnostic isotropic Gaussian source. As this source is conditioned on nei…
cs.RO2026
ConsisVLA-4D: Advancing Spatiotemporal Consistency in Efficient 3D-Perception and 4D-Reasoning for Robotic Manipulation
Wei Li, Jizhihui Liu, Li Yixing +3
Current Vision-Language-Action (VLA) models primarily focus on mapping 2D observations to actions, but exhibit notable limitations in spatiotemporal perception and reasoning: 1) sp…
cs.RO2026
ConLA: Contrastive Latent Action Learning from Human Videos for Robotic Manipulation
Weisheng Dai, Kai Lan, Jianyi Zhou +5
Vision-Language-Action (VLA) models achieve preliminary generalization through pretraining on large scale robot teleoperation datasets. However, acquiring datasets that comprehensi…