Jingjing Zhang

PL-HCL transforms the detection of inconsistencies in Agent Skills, boosting accuracy from 45% to nearly 90% and enhancing user trust in skill selection.

By preserving the semantics of pretrained models while achieving superior compositional generalization, InternVLA-A1.5 redefines how robots can learn and execute complex tasks.