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Key research priorities for multi-agent embodied autonomous driving (MAEAD): verifiable shared-state maintenance, robust intent and plan alignment, and safe coordinated action under communication and computing constraints in real-world deployment are motivated.
CoTIR achieves superior image restoration by internalizing reasoning processes, outperforming traditional methods even in complex degradation settings.
Achieve SOTA 3D scene reconstruction from collaborative driving views without calibration by treating multiple vehicles as a single, unstructured multi-camera system.
Visual RL agents can recover near-perfect performance even under severe, dynamically changing visual corruptions by learning to disentangle task-relevant foreground from perturbation artifacts.
