AI RESEARCH
TrafficRAG: A Multimodal RAG Framework for Traffic Accident Liability Determination
arXiv CS.AI
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ArXi:2606.01737v1 Announce Type: new Traffic accident liability analysis is a critical yet challenging task in intelligent transportation and legal assistance. Existing methods often suffer from low efficiency, subjective judgment, and inconsistent analysis results. Meanwhile, large language models are constrained by noisy video inputs and insufficient legal domain knowledge. To address these issues, this work presents TrafficRAG, a multimodal retrieval-augmented framework for automated traffic accident analysis and report generation.