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PlanT 2.0: Exposing Biases and Structural Flaws in Closed-Loop Driving

Description

Most recent work in autonomous driving has prioritized benchmark performance and methodological innovation over in-depth analysis of model failures, biases, and shortcut learning. This has led to incremental improvements without a deep understanding of the current failures. While it is straightforward to look at situations where the model fails, it is hard to understand the underlying reason. This motivates us to conduct a systematic study, where inputs to the model are perturbed and the predict

Source

http://arxiv.org/abs/2511.07292v1