TEMPO: Learning Temporal Context for Dynamic Robot Manipulation
DGX agentarXiv:2609.16864v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have achieved impressive performance in quasi-static manipulation, but struggle in dynamic manipulation tasks beca