OpenCodePapers
navsim-on-navsim-v2-navtest
Autonomous Driving
NavSim
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ModelName
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Do Better Visual Representations Always Lead to Better End-to-End Autonomous Driving?
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92.3
ViRA-Diffusion
2026-10-07
DriveStack-VLA: Render-Teacher Alignment for BEV-Based DeepStack Vision-Language-Action Model
91.0
DriveStack-VLA
2026-06-23
RISE: Adaptive Imagination for World Action Models
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90.8
RISE (extra data)
2026-08-20
SimWAM: A Simple World Action Model for End-to-End Autonomous Driving
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90.2
SimWAM
2026-08-07
Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives
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90.1
LTFv7
2026-05-19
PriorEye: Geospatial Visual Priors for End-to-End Autonomous Driving
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89.9
DrivoR + PriorEye
2026-06-30
FlowR2A: Learning Reward-to-Action Distribution for Multimodal Driving Planning
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88.9
FlowR2A (ResNet-34)
2026-06-23
DriveDreamer-Policy: A Geometry-Grounded World-Action Model for Unified Generation and Planning
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88.7
DriveDreamer-Policy
2026-04-02
HAD: Combining Hierarchical Diffusion with Metric-Decoupled RL for End-to-End Driving
88.6
HAD
2026-04-04
SimVTA: Simulation-Grounded Video-Trajectory Alignment for Driving World Action Models
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88.2
SimVTA (extra data)
2026-10-09
Drive-JEPA: Video JEPA Meets Multimodal Trajectory Distillation for End-to-End Driving
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87.8
Drive-JEPA ViT/L (extra data)
2026-01-29
SimScale: Learning to Drive via Real-World Simulation at Scale
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85.9
SimScale DiffusionDrive (pseudo-expert co-training) (extra data)
2025-11-28
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