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Research questionHow can urban trajectory systems screen collective anomalies cheaply yet provide source-verifiable event details on demand?Urban monitoring must process many trajectory windows with low latency, but anomaly scores alone do not establish what happened, who was involved, or where and when. Detailed diagnosis requires tracing claims back to source trajectories, creating tension between continuous screening and evidence-backed reporting.
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Latest papersRecent research connected to this question, newest first.TrajMind: Chaining Role-Specialized LoRAs for Fast-and-Slow Collective Trajectory Anomaly DiagnosisThe evidence concerns collective urban trajectory anomalies using a vision-language backbone with fast text-only screening and a slower source-verified diagnostic path. Reported results cover anomaly typing, localization, cross-city transfer, screening latency, and binary balanced accuracy; broader traffic-governance outcomes are not established.research paper · Sep 4, 2026
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