SCORP delivers 10-28% gains in safety and 2-7% in efficiency metrics on WOMD by using dual-path scene conditioning in diffusion planning plus variance-gated group-relative policy optimization for closed-loop stability.
MDG: Masked denoising generation for multi-agent behavior modeling in traffic environments
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Flow-ERD achieves state-of-the-art realism and diversity on the WOSAC benchmark by coupling agent-type-aware flow matching with entropy-regularized distillation that prevents mode collapse during closed-loop fine-tuning.
nuReasoning is a new real-world dataset and benchmark extending nuScenes/nuPlan with 20k clips and multi-type reasoning annotations to evaluate and improve reasoning in long-tail autonomous driving.
citing papers explorer
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SCORP: Scene-Consistent Multi-agent Diffusion Planning with Stable Online Reinforcement Post-Training for Cooperative Driving
SCORP delivers 10-28% gains in safety and 2-7% in efficiency metrics on WOMD by using dual-path scene conditioning in diffusion planning plus variance-gated group-relative policy optimization for closed-loop stability.
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Flow-ERD: Agent-type Aware Flow Matching with Entropy-Regularized Distillation for Diverse Traffic Simulation
Flow-ERD achieves state-of-the-art realism and diversity on the WOSAC benchmark by coupling agent-type-aware flow matching with entropy-regularized distillation that prevents mode collapse during closed-loop fine-tuning.
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nuReasoning: A Reasoning-Centric Dataset and Benchmark for Long-Tail Autonomous Driving
nuReasoning is a new real-world dataset and benchmark extending nuScenes/nuPlan with 20k clips and multi-type reasoning annotations to evaluate and improve reasoning in long-tail autonomous driving.