mlsanityData to 14 Oct 2026

Generalized Trajectory Scoring for End-to-end Multimodal Planning

arXiv 2506.06664 ↗First posted 7 Jun 2025cs.RO cs.CVcited by 67

Not on the map. Why?

Cited by 57 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

End-to-end multi-modal planning is a promising paradigm in autonomous driving, enabling decision-making with diverse trajectory candidates. A key component is a robust trajectory scorer capable of selecting the optimal trajectory from these candidates. While recent trajectory scorers focus on scoring either large sets of static trajectories or small sets of dynamically generated ones, both approaches face significant limitations in generalization. Static vocabularies provide effective coarse discretization but struggle to make fine-grained adaptation, while dynamic proposals offer detailed precision but fail to capture broader trajectory distributions. To overcome these challenges, we propose GTRS (Generalized Trajectory Scoring), a unified framework for end-to-end multi-modal planning that combines coarse and fine-grained trajectory evaluation. GTRS consists of three complementary innovations: (1) a diffusion-based trajectory generator that produces diverse fine-grained proposals; (2) a vocabulary generalization technique that trains a scorer on super-dense trajectory sets with dropout regularization, enabling its robust inference on smaller subsets; and (3) a sensor augmentation strategy that enhances out-of-domain generalization while incorporating refinement training for critical trajectory discrimination. As the winning solution of the Navsim v2 Challenge, GTRS demonstrates superior performance even with sub-optimal sensor inputs, approaching privileged methods that rely on ground-truth perception. Code will be available at https://github.com/NVlabs/GTRS.

Key facts. Cited by 67 papers in the map (data through 14 Oct 2026). Builds on 30 of its 33 references that are in the map. First posted on arXiv 7 Jun 2025.

Builds on

30 of 33 references.

References · 30

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  3. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  4. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,838
  5. 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,360
  6. 2022Planning-oriented Autonomous Drivingcited by 1,087
  7. 2023VAD: Vectorized Scene Representation for Efficient Autonomous Drivingcited by 622
  8. 2023DriveLM: Driving with Graph Visual Question Answeringcited by 536
  9. 2022TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Drivingcited by 485
  10. 2023EVA-02: A Visual Representation for Neon Genesiscited by 381
  11. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 354
  12. 2024DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Drivingcited by 334
18 more
  1. 2023Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detectioncited by 315
  2. 2024VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planningcited by 289
  3. 2021Is Pseudo-Lidar needed for Monocular 3D Object detection?cited by 249
  4. 2024Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillationcited by 249
  5. 2023Parting with Misconceptions about Learning-based Vehicle Motion Planningcited by 242
  6. 2023Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?cited by 242
  7. 2019An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detectioncited by 163
  8. 2025SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignmentcited by 150
  9. 2025Pseudo-Simulation for Autonomous Drivingcited by 150
  10. 2025Diffusion-Based Planning for Autonomous Driving with Flexible Guidancecited by 141
  11. 2025GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous Drivingcited by 120
  12. 2025Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillationcited by 96
  13. 2024CarLLaVA: Vision language models for camera-only closed-loop drivingcited by 57
  14. 2025Centaur: Robust End-to-End Autonomous Driving with Test-Time Trainingcited by 42
  15. 2025HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decodercited by 35
  16. 2025Learning Personalized Driving Styles via Reinforcement Learning from Human Feedbackcited by 17
  17. 2024Diffusion-Based Environment-Aware Trajectory Predictioncited by 14
  18. 2024QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Drivingcited by 11

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 18; 2026: 49.

67 papers.

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  1. 2025A Survey on Vision-Language-Action Models for Autonomous Drivingcited by 72
  2. 2025DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Drivingcited by 56
  3. 2026Driving on Registerscited by 44
  4. 2025SimScale: Learning to Drive via Real-World Simulation at Scalecited by 36
  5. 2026Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Drivingcited by 33
  6. 2025IRL-VLA: Training an Vision-Language-Action Policy via Reward World Modelcited by 31
  7. 2026SparseDriveV2: Scoring is All You Need for End-to-End Autonomous Drivingcited by 26
  8. 2025GuideFlow: Constraint-Guided Flow Matching for Planning in End-to-End Autonomous Drivingcited by 22
  9. 2025Reinforced Refinement with Self-Aware Expansion for End-to-End Autonomous Drivingcited by 19
  10. 2026DriveFine: Refining-Augmented Masked Diffusion VLA for Precise and Robust Drivingcited by 19
  11. 2025DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Drivingcited by 17
  12. 2026DriveFuture: Future-Aware Latent World Models for Autonomous Drivingcited by 17
38 more
  1. 2025PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Drivingcited by 16
  2. 2025Zero-Human Demonstration End-to-end Autonomous Driving with Trajectory Scorercited by 16
  3. 2025ResAD: Normalized Residual Trajectory Modeling for End-to-End Autonomous Drivingcited by 14
  4. 2025EvaDrive: Evolutionary Adversarial Policy Optimization for End-to-End Autonomous Drivingcited by 12
  5. 2025MindDrive: An All-in-One Framework Bridging World Models and Vision-Language Model for End-to-End Autonomous Drivingcited by 12
  6. 2026CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planningcited by 11
  7. 2026Metis: A Generalizable and Efficient World-Action Model for Autonomous Driving and Urban Navigationcited by 11
  8. 2025Percept-WAM: Perception-Enhanced World-Awareness-Action Model for Robust End-to-End Autonomous Drivingcited by 9
  9. 2026SafeDrive: Fine-Grained Safety Reasoning for End-to-End Driving in a Sparse Worldcited by 8
  10. 2026RAD-2: Scaling Reinforcement Learning in a Generator-Discriminator Frameworkcited by 8
  11. 2026Test-Time Trajectory Optimization for Autonomous Drivingcited by 7
  12. 2026GraphWorld: Long-Horizon Planning with World Models for End-to-End Autonomous Drivingcited by 6
  13. 2026HiST-VLA: A Hierarchical Spatio-Temporal Vision-Language-Action Model for End-to-End Autonomous Drivingcited by 5
  14. 2026DA-WAM: Decision-Aligned Future Latents for Driving World Modelscited by 5
  15. 2026HAD: Combining Hierarchical Diffusion with Metric-Decoupled RL for End-to-End Drivingcited by 4
  16. 2025DriveCritic: Towards Context-Aware, Human-Aligned Evaluation for Autonomous Driving with Vision-Language Modelscited by 3
  17. 2026DriveJudge: Rethinking Autonomous Driving Evaluation with Vision-Language Modelscited by 3
  18. 2026DriveZero: End-to-End Driving Beyond Human Demonstrationscited by 3
  19. 2025SimpleVSF: VLM-Scoring Fusion for Trajectory Prediction of End-to-End Autonomous Drivingcited by 2
  20. 2026Self-Imitated Diffusion Policy for Efficient and Robust Visual Navigationcited by 2
  21. 2026CRAFT: Counterfactual-to-Interactive Reinforcement Fine-Tuning for Driving Policiescited by 2
  22. 2026IDOL: Inverse-Dynamics-Guided Future Prediction for End-to-End Autonomous Drivingcited by 2
  23. 2026CLEAR: Cognition and Latent Evaluation for Adaptive Routing in End-to-End Autonomous Drivingcited by 2
  24. 2026DriveReward: A Comprehensive Dataset and Generative Vision-Language Reward Model for Autonomous Drivingcited by 2
  25. 2026PriorEye: Geospatial Visual Priors for End-to-End Autonomous Drivingcited by 2
  26. 2025Beyond Imitation: Constraint-Aware Trajectory Generation with Flow Matching For End-to-End Autonomous Drivingcited by 1
  27. 2025TrajMoE: Scene-Adaptive Trajectory Planning with Mixture of Experts and Reinforcement Learningcited by 1
  28. 2025Closing the Navigation Compliance Gap in End-to-end Autonomous Drivingcited by 1
  29. 2026ETA-VLA: Efficient Token Adaptation via Temporal Fusion and Intra-LLM Sparsification for Vision-Language-Action Modelscited by 1
  30. 2026FlowR2A: Learning Reward-to-Action Distribution for Multimodal Driving Planningcited by 1
  31. 2026Large Discrete Policy: Advancing Explicit Behavior Modeling with Stochastic Iterative Scoringcited by 1
  32. 2026MM-Future: Multi-Mode Joint World-Action Modeling for Autonomous Drivingcited by 1
  33. 2026The Constant Eye: Benchmarking and Bridging Appearance Robustness in Autonomous Drivingcited by 0
  34. 2026Off the Rails: Hijacking the Scoring Head in Generative End-to-End Driving Planners with Safety-Violating Adversarial Perturbationscited by 0
  35. 2026Driving the Wrong Way: Leveraging Interpretability in End2End Autonomous Driving Modelscited by 0
  36. 2026MOJITO: Modal Joint Learning for Unified End-to-End Autonomous Drivingcited by 0
  37. 2026Plug-and-Play Traffic Element Awareness for End-to-End Autonomous Drivingcited by 0
  38. 2026A Degradation-Tolerance Benchmark for Camera-Only End-to-End Drivingcited by 0

50 most cited of 67 All 67 (JSON)