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paperarXivTrust 82 · PrimaryPublished 4d agoLive · 3d ago

TAU-Agent: An Agentic Retrieval-Augmented Framework for Traffic Anomaly Understanding

Traffic Anomaly Understanding (TAU) requires models and systems to detect, reason about, and explain anomalous events in transportation videos. To address this challenge, we propose TAU-Agent, an agentic retrieval-augmented framework for traffic anomaly understanding. Given a task query, a central retrieval agent orchestrates two visual perception tools, namely a Video Captioning Tool and an Open-Vocabulary Tracking Tool, to retrieve and select query-relevant evidence, including captions, temporal intervals, and object trajectories. The selected evidence, together with sampled video frames and

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  • FuzzySimilar title/name (fuzzy) · 59%AgentCore-8B

    Fuzzy title match (0.73): “TAU-Agent: An Agentic Retrieval-Augmented Framework for Traf” ≈ “AgentCore-8B”

  • FuzzySimilar title/name (fuzzy) · 87%SWE-agent/SWE-agent

    Fuzzy title match (0.94): “TAU-Agent: An Agentic Retrieval-Augmented Framework for Traf” ≈ “SWE-agent/SWE-agent”

  • FuzzySimilar title/name (fuzzy) · 87%zhayujie/CowAgent

    Fuzzy title match (0.94): “TAU-Agent: An Agentic Retrieval-Augmented Framework for Traf” ≈ “zhayujie/CowAgent”

  • FuzzyOverlapping authors or contributors · 62%Zeyi-Lin/HivisionIDPhotos

    Shared author/contributor keys: lin

  • FuzzyOverlapping authors or contributors · 62%ray-project/ray

    Shared author/contributor keys: wang

  • FuzzyOverlapping authors or contributors · 62%bytedance/deer-flow

    Shared author/contributor keys: wang

  • LinkedLinked via arxiv author · 85%Yuqiang Lin

    TAU-Agent: An Agentic Retrieval-Augmented Framework for Traffic Anomaly Understanding

  • LinkedLinked via arxiv author · 85%Weiyan Shi

    TAU-Agent: An Agentic Retrieval-Augmented Framework for Traffic Anomaly Understanding

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