arXiv: cs.AI preprintsInternational11 November 2026
CASCADE: Constraint-Aware SCAffolded DEcomposition for Logical Anomaly Detection
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arXiv:2611.13820v1 Announce Type: cross Abstract: Logical Anomaly Detection (LAD) requires verifying whether all category-specific constraints, such as object counts, pairing relations, and measurement ranges, are satisfied by a query image given only a few normal references. Recent LAD methods based on Large Vision-Language Models (LVLMs) formulate this as checklist verification, decomposing the decision into independent textual checks. This decomposition, however, is text-only. Every item still reads the same unmodified query image, so the LVLM must extract different forms of visual evidence
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