BridgeGuard: Explicit Safety Drift for Diffusion-based Autonomous Driving
cs.AI
Submitted: 2026-10-08
Updated: 2026-10-08
Code: https://github.com/OpenDriveLab/DriveLM
Sources
- ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst
- SparseDriveV2: Scoring is All You Need for End-to-End Autonomous Driving
- GenAD: Generative End-to-End Autonomous Driving
- Unleashing the Potential of Diffusion Models for End-to-End Autonomous Driving
- Hidden Biases of End-to-End Driving Datasets
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems