PAVE: Predictive Alignment and Value-Guided Evolution for World-Action Policies
Research
Source: arXiv cs.ROPublish time unverified
arXiv:2608.30378v1 Announce Type: new Abstract: Direct vision-language-action policies generate continuous robot actions efficiently, but standard behavior cloning leaves two complementary gaps: their representations are not explicitly required to describe how the scene evolves over multiple time scales, and deployment trajectories of unequal quality are often reused without separating useful dynamics from undesirable behavior.