arXiv cs.CV
· Papers
PoseVLA: Universal Pose Pretraining for Generalizable Vision-Language-Action Policies
arXiv:2602.19710v3 Announce Type: replace Abstract: Existing Vision-Language-Action (VLA) models often suffer from feature collapse and low training efficiency because they entangle high-level perception with sparse, embodiment-specific action supervision. Since these models typically rely on VLM backbones optimized fo