Deterministic PRM guidance for discrete diffusion reasoning underperforms simpler ORM reranking because PRMs score weak intermediate states poorly and judge final outputs worse than outcome verifiers, reducing accuracy by up to 12.69 percentage points.
SIGMA uses semantic feature differencing with instruction-guided spatial priors to generate manipulation masks from edited images, producing a 1.1M training set that improves detectors by +18.34% F1.
SPACE defines pivot-aligned coordinate-free embeddings and adaptive decoding to unify neural routing across symmetric and asymmetric VRPs, achieving strong zero-shot generalization on 110 variants.