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Imagine cities teaching cars to see: this work demonstrates a label-free 3D perception pipeline where roadside sensors train autonomous vehicles, achieving impressive detection accuracy without manual annotation.
Ditch the anchors and NMS: AutoReg3D reimagines 3D object detection as a sequence generation problem, opening the door for language-model techniques in 3D perception.
Forget expensive human annotations or hallucination-prone LLM-generated data: rule-generated synthetic data can teach LLMs to compose knowledge and significantly boost multi-hop reasoning on real-world tasks.
