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Open access Aug 2026

Data-Centric Autonomous Driving: A Data-Utilization Framework for Learning from Large-Scale Driving Logs

Closed-loop autonomous driving increasingly combines model-centric architectural development with data-centric learning. These two directions are complementary: model-centric methods improve representation, prediction, planning, and control capabilities, whereas data-centric methods improve how training samples, superv...

Yu Li, Wenhao Kang · 1 citation
Preprint Aug 2026

CRUISE: Vision-Language Model-Guided Uncertainty-Aware Cross-Modal Sensor Fusion for Robust Autonomous Driving

Modern autonomous vehicles are equipped with multiple sensors, such as cameras, LiDAR, and radar, for comprehensive environmental perception. However, robust cross-modal feature fusion remains a critical challenge, as the reliability of each sensor varies significantly across diverse real-world driving conditions, incl...

Junyao Wang, Yulin Xu, Yu Li et al. · 1 citation

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