Source record

Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2607.18142.

Pipeline notes

The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.

Introduces O-VAD, a training-free agentic framework for industrial video anomaly detection that tracks spatial-temporal dynamics of objects and reasons over object-wise temporal state trajectories to identify anomalies, outperforming frontier VLMs and existing methods on three IVAD datasets.

Training-free design with object-state trajectory reasoning is a transferable pattern for agentic systems, though the industrial video focus narrows direct workstation relevance.

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