A per-head Fisher-ratio score selects steering that nearly matches fine-tuning

Cai et al. define a per-attention-head Representational Separability Analysis score (inter- over intra-cluster scatter) quantifying normal/anomalous manifold entanglement in a frozen InternVL3-8B [cai-etal-2026-steervad-manifold-rectification] The score selects which heads receive a targeted anisotropic-scaling causal intervention that stretches or compresses the manifold along discriminative axes [cai-etal-2026-steervad-manifold-rectification] SteerVAD reaches 87.15% AUC on UCF-Crime, nearly matching a fully fine-tuned baseline (Holmes-VAD 89.51%) with about 1% of its training data [cai-etal-2026-steervad-manifold-rectification] Ablating the anisotropic steering degrades AUC, and a linear-classifier-on-raw-features baseline reaches only 81.33% [cai-etal-2026-steervad-manifold-rectification]