Search papers, labs, and topics across Lattice.
2
0
5
11
MLLMs stumble badly when asked to reason about safety in lab settings, dropping 32% in performance compared to general knowledge, revealing a critical gap for real-world deployment.
By decoupling camera and manipulation actions and training them in a coordinated manner, SaPaVe achieves significantly higher success rates in real-world robotic manipulation tasks compared to existing end-to-end vision-language-action models.
