SOURCE-LINKED INTELLIGENCE
Symmetry-Aware Likelihood-Orbit Aggregation for Selective Left-Right Claim Verification
Frozen vision-language models (VLMs) remain unreliable on fine-grained left-right claims, and raw claim likelihoods need not reliably rank verification errors. After a horizontal-reflection intervention is fixed, how should its induced likelihood measurements be combined into a selective verification signal? We introduce Relation-Orbit, a closed-form contrast with no learned fusion parameters that assigns eight normalized likelihoods to query-supporting and counterfactual roles determined by reflection, inverse relation, and entity exchange. A claim is asserted only when the signed contrast ex
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T11:19:03.000Z
First collected: 2026-09-20T08:40:59.508Z. This is not the publication date.