FoodMonitor: Benchmarking MLLMs for Explainable Compliance Analysis 事件

FoodMonitor: Benchmarking MLLMs for Explainable Compliance Analysis arXiv:2605.24503v1 Announce Type: new Abstract: 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 sc