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Found 4 papers, 0 papers with code
TPLLM: A Traffic Prediction Framework Based on Pretrained Large Language Models
Traffic prediction constitutes a pivotal facet within the purview of Intelligent Transportation Systems (ITS), and the attainment of highly precise predictions holds profound significance for efficacious traffic management.
Detecting Out-of-Distribution Samples via Conditional Distribution Entropy with Optimal Transport
When deploying a trained machine learning model in the real world, it is inevitable to receive inputs from out-of-distribution (OOD) sources.
AccidentGPT: Accident Analysis and Prevention from V2X Environmental Perception with Multi-modal Large Model
For human-driven vehicles, we offer proactive long-range safety warnings and blind-spot alerts while also providing safety driving recommendations and behavioral norms through human-machine dialogue and interaction.
OT-Filter: An Optimal Transport Filter for Learning With Noisy Labels
Learning with noisy labels is challenging because the performance of the deep neural networks (DNN) drastically degenerates, due to confirmation bias caused by the network memorization over noisy labels.
