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AutoWorld: Learning Multi-Agent Traffic Simulation with Self-Supervised World Models
Simulation with realistic traffic agents is essential for validating autonomous driving systems. Existing data-driven simulators learn agent behavior from higher-level abstractions such as 3D bounding boxes and polylines, inferred by upstream perception pipelines. These lossy abstractions discard se
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