RoboFollow diagnoses nine embodied policies in high-entropy scenes: near-saturated L0, sharp L1–L3 intent drops, and no fix from stronger VLMs or existing optimizations
The work introduces RoboFollow, a diagnostic benchmark combining high scene entropy, an L0–L3 hierarchical perturbation protocol, and stage-wise Intent/Execution scoring, and finds across nine VLA and WAM policies that strong in-distribution L0 performance does not transfer to L1–L3, with stronger VLM backbones, QA co-training, LangForce, and classifier-free guidance all failing to close the gap.