2 papers
cs.LG2026
ADV-0: Closed-Loop Min-Max Adversarial Training for Long-Tail Robustness in Autonomous Driving
Tong Nie, Yihong Tang, Junlin He +5
Deploying autonomous driving systems requires robustness against long-tail scenarios that are rare but safety-critical. While adversarial training offers a promising solution, exis…
cs.RO2024
InterHub: A Naturalistic Trajectory Dataset with Dense Interaction for Autonomous Driving
Xiyan Jiang, Xiaocong Zhao, Yiru Liu +4
The driving interaction-a critical yet complex aspect of daily driving-lies at the core of autonomous driving research. However, real-world driving scenarios sparsely capture rich…