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cs.CV2025
Structured Labeling Enables Faster Vision-Language Models for End-to-End Autonomous Driving
Hao Jiang, Chuan Hu, Yukang Shi +4
Vision-Language Models (VLMs) offer a promising approach to end-to-end autonomous driving due to their human-like reasoning capabilities. However, troublesome gaps remains between…
cs.CV2025
Active Learning from Scene Embeddings for End-to-End Autonomous Driving
Wenhao Jiang, Duo Li, Menghan Hu +3
In the field of autonomous driving, end-to-end deep learning models show great potential by learning driving decisions directly from sensor data. However, training these models req…