ATLAS: A Large-Scale Evaluation Benchmark for Adversarial LiDAR Perception

ArXi:2606.02924v1 Announce Type: new Autonomous driving perception is typically evaluated on clean benchmark data, yet real-world deployment requires robustness to rare, structured, and potentially adversarial sensor anomalies. This gap is especially critical for LiDAR, where external actors can physically manipulate the sensing process to induce black-box perception failures without accessing the model. Existing LiDAR benchmarks provide little visibility into this failure mode.