FoodMonitor: Benchmarking MLLMs for Explainable Compliance Analysis

ArXi:2605.24503v1 Announce Type: cross As AI-powered compliance monitoring becomes increasingly important in public governance and industrial safety, the ability to provide verifiable evidence and traceable accountability signals is essential. However, existing video anomaly detection datasets focus on event-level binary classification, lacking the rule-driven, explainable analysis required for real-world compliance scenarios. We