{"total":67,"rows":[{"id":"2506.24044","title":"A Survey on Vision-Language-Action Models for Autonomous Driving","created":"2025-06-30","cited_by_count":72,"area":"mllm"},{"id":"2512.07745","title":"DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Driving","created":"2025-12-08","cited_by_count":56,"area":"diffusion"},{"id":"2601.05083","title":"Driving on Registers","created":"2026-01-08","cited_by_count":44,"area":"driving"},{"id":"2511.23369","title":"SimScale: Learning to Drive via Real-World Simulation at Scale","created":"2025-11-28","cited_by_count":36,"area":null},{"id":"2603.24581","title":"Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Driving","created":"2026-03-25","cited_by_count":33,"area":"wm"},{"id":"2508.06571","title":"IRL-VLA: Training an Vision-Language-Action Policy via Reward World Model","created":"2025-08-07","cited_by_count":31,"area":"wm"},{"id":"2603.29163","title":"SparseDriveV2: Scoring is All You Need for End-to-End Autonomous Driving","created":"2026-03-31","cited_by_count":26,"area":"driving"},{"id":"2511.18729","title":"GuideFlow: Constraint-Guided Flow Matching for Planning in End-to-End Autonomous Driving","created":"2025-11-24","cited_by_count":22,"area":"diffusion"},{"id":"2506.09800","title":"Reinforced Refinement with Self-Aware Expansion for End-to-End Autonomous Driving","created":"2025-06-11","cited_by_count":19,"area":"driving"},{"id":"2602.14577","title":"DriveFine: Refining-Augmented Masked Diffusion VLA for Precise and Robust Driving","created":"2026-02-16","cited_by_count":19,"area":"vla"},{"id":"2507.04049","title":"DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving","created":"2025-07-05","cited_by_count":17,"area":"diffusion"},{"id":"2605.09701","title":"DriveFuture: Future-Aware Latent World Models for Autonomous Driving","created":"2026-05-10","cited_by_count":17,"area":"wm"},{"id":"2507.17596","title":"PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving","created":"2025-07-23","cited_by_count":16,"area":"driving"},{"id":"2510.24108","title":"Zero-Human Demonstration End-to-end Autonomous Driving with Trajectory Scorer","created":"2025-10-28","cited_by_count":16,"area":"driving"},{"id":"2510.08562","title":"ResAD: Normalized Residual Trajectory Modeling for End-to-End Autonomous Driving","created":"2025-10-09","cited_by_count":14,"area":"driving"},{"id":"2508.09158","title":"EvaDrive: Evolutionary Adversarial Policy Optimization for End-to-End Autonomous Driving","created":"2025-08-05","cited_by_count":12,"area":"driving"},{"id":"2512.04441","title":"MindDrive: An All-in-One Framework Bridging World Models and Vision-Language Model for End-to-End Autonomous Driving","created":"2025-12-04","cited_by_count":12,"area":"wm"},{"id":"2605.15120","title":"CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planning","created":"2026-05-14","cited_by_count":11,"area":"driving"},{"id":"2606.15869","title":"Metis: A Generalizable and Efficient World-Action Model for Autonomous Driving and Urban Navigation","created":"2026-06-14","cited_by_count":11,"area":"wm"},{"id":"2511.19221","title":"Percept-WAM: Perception-Enhanced World-Awareness-Action Model for Robust End-to-End Autonomous Driving","created":"2025-11-24","cited_by_count":9,"area":"mllm"},{"id":"2602.18887","title":"SafeDrive: Fine-Grained Safety Reasoning for End-to-End Driving in a Sparse World","created":"2026-02-21","cited_by_count":8,"area":"driving"},{"id":"2604.15308","title":"RAD-2: Scaling Reinforcement Learning in a Generator-Discriminator Framework","created":"2026-04-16","cited_by_count":8,"area":"deeprl"},{"id":"2606.07170","title":"Test-Time Trajectory Optimization for Autonomous Driving","created":"2026-06-05","cited_by_count":7,"area":"driving"},{"id":"2606.16274","title":"GraphWorld: Long-Horizon Planning with World Models for End-to-End Autonomous Driving","created":"2026-06-15","cited_by_count":6,"area":"wm"},{"id":"2602.13329","title":"HiST-VLA: A Hierarchical Spatio-Temporal Vision-Language-Action Model for End-to-End Autonomous Driving","created":"2026-02-11","cited_by_count":5,"area":"vla"},{"id":"2608.19085","title":"DA-WAM: Decision-Aligned Future Latents for Driving World Models","created":"2026-08-19","cited_by_count":5,"area":"wm"},{"id":"2604.03581","title":"HAD: Combining Hierarchical Diffusion with Metric-Decoupled RL for End-to-End Driving","created":"2026-04-04","cited_by_count":4,"area":"driving"},{"id":"2510.13108","title":"DriveCritic: Towards Context-Aware, Human-Aligned Evaluation for Autonomous Driving with Vision-Language Models","created":"2025-10-15","cited_by_count":3,"area":"mllm"},{"id":"2606.17362","title":"DriveJudge: Rethinking Autonomous Driving Evaluation with Vision-Language Models","created":"2026-06-15","cited_by_count":3,"area":"lr"},{"id":"2609.06055","title":"DriveZero: End-to-End Driving Beyond Human Demonstrations","created":"2026-09-05","cited_by_count":3,"area":"driving"},{"id":"2510.17191","title":"SimpleVSF: VLM-Scoring Fusion for Trajectory Prediction of End-to-End Autonomous Driving","created":"2025-10-20","cited_by_count":2,"area":"driving"},{"id":"2601.22965","title":"Self-Imitated Diffusion Policy for Efficient and Robust Visual Navigation","created":"2026-01-30","cited_by_count":2,"area":"diffusion"},{"id":"2605.04470","title":"CRAFT: Counterfactual-to-Interactive Reinforcement Fine-Tuning for Driving Policies","created":"2026-05-06","cited_by_count":2,"area":"driving"},{"id":"2605.31476","title":"IDOL: Inverse-Dynamics-Guided Future Prediction for End-to-End Autonomous Driving","created":"2026-05-29","cited_by_count":2,"area":"wm"},{"id":"2606.06219","title":"CLEAR: Cognition and Latent Evaluation for Adaptive Routing in End-to-End Autonomous Driving","created":"2026-06-04","cited_by_count":2,"area":"driving"},{"id":"2606.08525","title":"DriveReward: A Comprehensive Dataset and Generative Vision-Language Reward Model for Autonomous Driving","created":"2026-06-07","cited_by_count":2,"area":"driving"},{"id":"2606.31830","title":"PriorEye: Geospatial Visual Priors for End-to-End Autonomous Driving","created":"2026-06-30","cited_by_count":2,"area":"driving"},{"id":"2510.26292","title":"Beyond Imitation: Constraint-Aware Trajectory Generation with Flow Matching For End-to-End Autonomous Driving","created":"2025-10-30","cited_by_count":1,"area":"diffusion"},{"id":"2512.07135","title":"TrajMoE: Scene-Adaptive Trajectory Planning with Mixture of Experts and Reinforcement Learning","created":"2025-12-08","cited_by_count":1,"area":"moe"},{"id":"2512.10660","title":"Closing the Navigation Compliance Gap in End-to-end Autonomous Driving","created":"2025-12-11","cited_by_count":1,"area":"driving"},{"id":"2603.25766","title":"ETA-VLA: Efficient Token Adaptation via Temporal Fusion and Intra-LLM Sparsification for Vision-Language-Action Models","created":"2026-03-26","cited_by_count":1,"area":"vla"},{"id":"2606.24231","title":"FlowR2A: Learning Reward-to-Action Distribution for Multimodal Driving Planning","created":"2026-06-23","cited_by_count":1,"area":null},{"id":"2609.07049","title":"Large Discrete Policy: Advancing Explicit Behavior Modeling with Stochastic Iterative Scoring","created":"2026-09-07","cited_by_count":1,"area":null},{"id":"2609.20377","title":"MM-Future: Multi-Mode Joint World-Action Modeling for Autonomous Driving","created":"2026-09-17","cited_by_count":1,"area":"wm"},{"id":"2602.12563","title":"The Constant Eye: Benchmarking and Bridging Appearance Robustness in Autonomous Driving","created":"2026-02-13","cited_by_count":0,"area":"driving"},{"id":"2606.30807","title":"Off the Rails: Hijacking the Scoring Head in Generative End-to-End Driving Planners with Safety-Violating Adversarial Perturbations","created":"2026-06-29","cited_by_count":0,"area":"driving"},{"id":"2607.06328","title":"Driving the Wrong Way: Leveraging Interpretability in End2End Autonomous Driving Models","created":"2026-07-07","cited_by_count":0,"area":"driving"},{"id":"2607.23511","title":"MOJITO: Modal Joint Learning for Unified End-to-End Autonomous Driving","created":"2026-07-26","cited_by_count":0,"area":"driving"},{"id":"2608.18035","title":"Plug-and-Play Traffic Element Awareness for End-to-End Autonomous Driving","created":"2026-08-18","cited_by_count":0,"area":"driving"},{"id":"2608.29005","title":"A Degradation-Tolerance Benchmark for Camera-Only End-to-End Driving","created":"2026-08-29","cited_by_count":0,"area":"driving"},{"id":"2609.01799","title":"Designing Versatile Samples for Learned Trajectory Scoring","created":"2026-09-01","cited_by_count":0,"area":"driving"},{"id":"2609.22317","title":"EditWM: Event-Decomposed World Modeling with Incremental Correction for End-to-End Autonomous Driving","created":"2026-09-15","cited_by_count":0,"area":"wm"},{"id":"2609.26618","title":"NavSafe-$\\infty$: Benchmarking Closed-Loop Driving Safety in Photorealistic Environments","created":"2026-09-22","cited_by_count":0,"area":"driving"},{"id":"2609.30818","title":"Evaluation Is All You Need for Multi-Modal Autonomous Driving","created":"2026-09-25","cited_by_count":0,"area":"driving"},{"id":"2609.31374","title":"RECAST: From Log Replay to Closed-Loop Driving Simulation with View-Complete Actors","created":"2026-09-25","cited_by_count":0,"area":"driving"},{"id":"2609.33189","title":"When an Evaluation Rule Writes Training Labels: Measuring Human-Reference Forgiveness in NAVSIM","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2609.33737","title":"MomWorld: Momentum-Aware Latent World Model for Long-Horizon Autonomous Driving","created":"2026-09-27","cited_by_count":0,"area":"wm"},{"id":"2609.33854","title":"ReDrive: Shaping Representations with World Modeling for End-to-End Driving","created":"2026-09-27","cited_by_count":0,"area":"wm"},{"id":"2609.34440","title":"When the Score Becomes the Target: Rethinking Metric Validity in Autonomous Driving","created":"2026-09-28","cited_by_count":0,"area":"driving"},{"id":"2609.36438","title":"World4Scorer: Outcome-Grounded World Modeling for Autonomous Driving","created":"2026-09-29","cited_by_count":0,"area":"wm"},{"id":"2609.36851","title":"RoXDrive: Closed-Loop Reinforcement Learning for End-to-End Autonomous Driving via Action-Faithful Rollouts","created":"2026-09-29","cited_by_count":0,"area":"wm"},{"id":"2610.11060","title":"AffordDrive3D: Affordance-Aware World-Action Modeling with Spatial Understanding","created":"2026-10-08","cited_by_count":0,"area":"wm"},{"id":"2610.11382","title":"PlanWAM: Planning-Shaped Future Representations for End-to-End Autonomous Driving","created":"2026-10-08","cited_by_count":0,"area":"wm"},{"id":"2610.13232","title":"FPD-Drive: Future Policy Distillation for End-to-End Autonomous Driving","created":"2026-10-09","cited_by_count":0,"area":"driving"},{"id":"2610.14802","title":"YOUDrive: Driving Style as a Composable Direction for End-to-End Autonomous Driving","created":"2026-10-10","cited_by_count":0,"area":"driving"},{"id":"2610.14871","title":"MORE: Learning Motion-Oriented Registers for Driving World Models and Planning","created":"2026-10-10","cited_by_count":0,"area":"wm"},{"id":"2610.16908","title":"ConDenseDrive: Knowledge-Dense, Token-Sparse Visual Encoder for End-to-End Autonomous Driving","created":"2026-10-12","cited_by_count":0,"area":"driving"}],"next_cursor":null}