Cross-expert robustness of recoverability-based selection

Establish whether the benefit of interventional recoverability for Vision-Language-Action recovery-data selection and the stability of recoverability frontiers persist across different recovery experts.

Background

The Kintsugi-VLA framework defines recoverability relative to a particular privileged recovery expert rather than as an intrinsic property of a simulator state. The paper’s audit finds substantial variation in state-wise recovery rankings among nominally competent teachers, with pairwise Spearman correlations ranging from 0.103 to 0.693. Because changing the expert may alter difficulty bins, selected states, and generated demonstrations, the robustness of the downstream VLA benefit and of stable recoverability frontiers across experts remains unresolved.