QVAD: A Question-Centric Agentic Framework for Efficient and Training-Free Video Anomaly Detection explores A question-centric agentic framework that uses dynamic dialogue to enable lightweight VLMs to achieve state-of-the-art video anomaly detection with high inference speeds and minimal memory footprints.. Commercial viability score: 7/10 in Video Anomaly Detection.
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Page Freshness
Canonical route: /paper/qvad-a-question-centric-agentic-framework-for-efficient-and-training-free-video-anomaly-detection
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Agent Handoff
Canonical ID qvad-a-question-centric-agentic-framework-for-efficient-and-training-free-video-anomaly-detection | Route /paper/qvad-a-question-centric-agentic-framework-for-efficient-and-training-free-video-anomaly-detection
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/qvad-a-question-centric-agentic-framework-for-efficient-and-training-free-video-anomaly-detectionMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.03040"
}
}source_context
{
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"mode": "paper",
"query": "QVAD: A Question-Centric Agentic Framework for Efficient and Training-Free Video Anomaly Detection",
"normalized_query": "2604.03040",
"route": "/paper/qvad-a-question-centric-agentic-framework-for-efficient-and-training-free-video-anomaly-detection",
"paper_ref": "qvad-a-question-centric-agentic-framework-for-efficient-and-training-free-video-anomaly-detection",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
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Dimensions overall score 7.0
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