GaussianDWM uses 3D Gaussians with embedded linguistic features, language-guided sampling, and dual-condition generation for unified scene understanding and multi-modal output in driving world models.
Drivegpt4: Interpretable end-to-end autonomous driving via large language model.IEEE Robotics and Automation Let- ters, 2024
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AutoDrive-R² adds four-step CoT reasoning with self-reflection to VLA models via SFT on nuScenesR²-6K and GRPO RL under spatial, dynamic, and smoothness rewards, reporting SOTA results on nuScenes and Waymo.
citing papers explorer
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GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation
GaussianDWM uses 3D Gaussians with embedded linguistic features, language-guided sampling, and dual-condition generation for unified scene understanding and multi-modal output in driving world models.
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AutoDrive-R$^2$: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving
AutoDrive-R² adds four-step CoT reasoning with self-reflection to VLA models via SFT on nuScenesR²-6K and GRPO RL under spatial, dynamic, and smoothness rewards, reporting SOTA results on nuScenes and Waymo.