OmniV2X is a generative foundation planner for end-to-end cooperative driving that achieves state-of-the-art performance on DAIR-V2X-Seq using less than 10% of the fine-tune V2X dataset and less than 1% of the communication bandwidth.
V2X-VLM: End-to-End V2X Cooperative Au- tonomous Driving Through Large Vision-Language Models,
2 Pith papers cite this work. Polarity classification is still indexing.
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A survey synthesizing LLM and MM-LLM uses in transportation operations, mobility services, and decision support while noting challenges like data heterogeneity and real-time needs.
citing papers explorer
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OmniV2X: A Generative Foundation Planner for Efficient End-to-End Cooperative Driving
OmniV2X is a generative foundation planner for end-to-end cooperative driving that achieves state-of-the-art performance on DAIR-V2X-Seq using less than 10% of the fine-tune V2X dataset and less than 1% of the communication bandwidth.
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Large Language Models in Transportation Systems Management and Operations: From Text Reasoning to Multi-modal Decision Support
A survey synthesizing LLM and MM-LLM uses in transportation operations, mobility services, and decision support while noting challenges like data heterogeneity and real-time needs.