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arXiv Computer Vision By Zhouzhi Xiong, Chuxi Zhang, Weizhen He, Yi Chen, Qi Li, Donglian Qi

Symmetry-Aware Likelihood-Orbit Aggregation for Selective Left-Right Claim Verification

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The paper introduces Relation‑Orbit, a symmetry‑aware method for aggregating likelihoods from frozen vision‑language models to verify fine‑grained left‑right claims. It uses a closed‑form contrast that assigns eight normalized likelihoods based on reflection, inverse relation, and entity exchange, and asserts a claim only when the signed contrast exceeds a threshold chosen via Clopper‑Pearson bounds. Experiments on VSR, GQA, and LLaVA‑1.5/COCO show that Relation‑Orbit achieves higher mean test coverage at a 10% selective‑risk calibration target compared to an all‑eight Orbit‑Max baseline across multiple dataset‑backbone settings.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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