Proposed SOSPA and PLD metrics replace Chamfer-distance mAP with order-aware geometry evaluation and soft assignment, revealing detection, not geometry, as online mapping's dominant bottleneck.
Diffusion models learn high-variance classes first, but sampling imbalance can reverse this ordering and delay minority class learning, causing uneven memorization.