Prior Directions: Separating Geometric Identification from Behavioral Efficacy in Visual Revision
Vision-language models can remain anchored to stale verbal priors even when current visual evidence supports a different answer. We use this controlled revision failure to ask whether the subspace that best captures recurrent prior-induced representation change is also uniquely more behaviorally effective. Across four models, paired prior and reference states define Prior Directions, a compact low-rank geometry that, at rank 32, spans only 0.78% of the state dimensions yet captures 49.7% to 64.0% of held-out displacement energy. Matched correspondence improves held-out capture at every tested rank in all four models; across 20 permutation seeds, this advantage remains positive in all 15 a...
| Authors | Weile Gong, Zijian Lu, Mingcai Chen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 29 July 2026 |
| Last updated at source | 26 September 2026 |
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