{"total":54,"rows":[{"id":"2502.13144","title":"RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learning","created":"2025-02-18","cited_by_count":79,"area":"driving"},{"id":"2505.15111","title":"iPad: Iterative Proposal-centric End-to-End Autonomous Driving","created":"2025-05-21","cited_by_count":42,"area":"driving"},{"id":"2509.17940","title":"DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Driving","created":"2025-09-22","cited_by_count":39,"area":"driving"},{"id":"2601.22032","title":"Drive-JEPA: Video JEPA Meets Multimodal Trajectory Distillation for End-to-End Driving","created":"2026-01-29","cited_by_count":30,"area":"driving"},{"id":"2506.23982","title":"StyleDrive: Towards Driving-Style Aware Benchmarking of End-To-End Autonomous Driving","created":"2025-06-30","cited_by_count":21,"area":"driving"},{"id":"2412.09647","title":"Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model","created":"2024-12-11","cited_by_count":14,"area":"driving"},{"id":"2503.13047","title":"InsightDrive: Insight Scene Representation for End-to-End Autonomous Driving","created":"2025-03-17","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":"2505.19516","title":"DiffE2E: Rethinking End-to-End Driving with a Hybrid Action Diffusion and Supervised Policy","created":"2025-05-26","cited_by_count":9,"area":"driving"},{"id":"2512.00723","title":"TrajDiff: End-to-end Autonomous Driving without Perception Annotation","created":"2025-11-30","cited_by_count":8,"area":"driving"},{"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":"2603.14972","title":"Learning from Mistakes: Post-Training for Driving VLA with Takeover Data","created":"2026-03-16","cited_by_count":8,"area":"driving"},{"id":"2605.19771","title":"Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives","created":"2026-05-19","cited_by_count":8,"area":"driving"},{"id":"2511.21584","title":"Model-Based Policy Adaptation for Closed-Loop End-to-End Autonomous Driving","created":"2025-11-26","cited_by_count":7,"area":"driving"},{"id":"2510.23205","title":"VR-Drive: Viewpoint-Robust End-to-End Driving with Feed-Forward 3D Gaussian Splatting","created":"2025-10-27","cited_by_count":6,"area":"driving"},{"id":"2509.23922","title":"DriveE2E: Closed-Loop Benchmark for End-to-End Autonomous Driving through Real-to-Simulation","created":"2025-09-28","cited_by_count":5,"area":"driving"},{"id":"2512.06865","title":"Spatial Retrieval Augmented Autonomous Driving","created":"2025-12-07","cited_by_count":5,"area":"driving"},{"id":"2505.21581","title":"CogAD: Cognitive-Hierarchy Guided End-to-End Autonomous Driving","created":"2025-05-27","cited_by_count":4,"area":"driving"},{"id":"2511.13306","title":"DAP: A Discrete-token Autoregressive Planner for Autonomous Driving","created":"2025-11-17","cited_by_count":4,"area":"driving"},{"id":"2603.13399","title":"FlowAD: Ego-Scene Interactive Modeling for Autonomous Driving","created":"2026-03-11","cited_by_count":4,"area":"driving"},{"id":"2603.13842","title":"Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving","created":"2026-03-14","cited_by_count":4,"area":"driving"},{"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":"2505.18945","title":"Echo Planning for Autonomous Driving: From Current Observations to Future Trajectories and Back","created":"2025-05-25","cited_by_count":3,"area":"driving"},{"id":"2507.00709","title":"TopoStreamer: Temporal Lane Segment Topology Reasoning in Autonomous Driving","created":"2025-07-01","cited_by_count":3,"area":"driving"},{"id":"2510.17148","title":"DiffVLA++: Bridging Cognitive Reasoning and End-to-End Driving through Metric-Guided Alignment","created":"2025-10-20","cited_by_count":3,"area":"driving"},{"id":"2603.11417","title":"Zero-Shot Cross-City Generalization in End-to-End Autonomous Driving: Self-Supervised versus Supervised Representations","created":"2026-03-12","cited_by_count":3,"area":"driving"},{"id":"2605.21139","title":"Distill to Think, Foresee to Act: Cognitive-Physical Reinforcement Learning for Autonomous Driving","created":"2026-05-20","cited_by_count":3,"area":"driving"},{"id":"2511.01334","title":"Embodied Cognition Augmented End2End Autonomous Driving","created":"2025-11-03","cited_by_count":2,"area":"driving"},{"id":"2603.07686","title":"UniUncer: Unified Dynamic Static Uncertainty for End to End Driving","created":"2026-03-08","cited_by_count":2,"area":"driving"},{"id":"2608.03084","title":"SUV: Future Scene Understanding as Video Generation for End-to-End Driving","created":"2026-08-04","cited_by_count":2,"area":"driving"},{"id":"2508.06113","title":"GMF-Drive: Gated Mamba Fusion with Spatial-Aware BEV Representation for End-to-End Autonomous Driving","created":"2025-08-08","cited_by_count":1,"area":"driving"},{"id":"2511.22865","title":"SUPER-AD: Semantic Uncertainty-aware Planning for End-to-End Robust Autonomous Driving","created":"2025-11-28","cited_by_count":1,"area":"driving"},{"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":"2602.03112","title":"A Unified Candidate Set with Scene-Adaptive Refinement via Diffusion for End-to-End Autonomous Driving","created":"2026-02-03","cited_by_count":1,"area":"driving"},{"id":"2602.18757","title":"Driving Like Yourself: A Benchmark for Closed-Loop Personalized End-to-End Autonomous Driving","created":"2026-02-21","cited_by_count":1,"area":"driving"},{"id":"2605.13646","title":"Causality-Aware End-to-End Autonomous Driving via Ego-Centric Joint Scene Modeling","created":"2026-05-13","cited_by_count":1,"area":"driving"},{"id":"2605.21061","title":"Grounding Driving VLA via Inverse Kinematics","created":"2026-05-20","cited_by_count":1,"area":"driving"},{"id":"2609.25831","title":"Sometimes You Gotta Run Before You Can Walk: Run-then-Walk Scheduling Strategy for VLM Autonomous Driving","created":"2026-09-22","cited_by_count":1,"area":"driving"},{"id":"2508.11453","title":"EvoPSF: Online Evolution of Autonomous Driving Models via Planning-State Feedback","created":"2025-08-15","cited_by_count":0,"area":"driving"},{"id":"2602.06214","title":"Addressing the Waypoint-Action Gap in End-to-End Autonomous Driving via Vehicle Motion Models","created":"2026-02-05","cited_by_count":0,"area":"driving"},{"id":"2604.00597","title":"Towards Viewpoint-Robust End-to-End Autonomous Driving with 3D Foundation Model Priors","created":"2026-04-01","cited_by_count":0,"area":"driving"},{"id":"2605.16737","title":"DriveSafer: End-to-End Autonomous Driving with Safety Guidance","created":"2026-05-16","cited_by_count":0,"area":"driving"},{"id":"2606.04884","title":"D$^3$-MoE:Dual Disentangled Diffusion Mixture-of-Experts for Style-Controllable End-to-End Autonomous Driving","created":"2026-06-03","cited_by_count":0,"area":"driving"},{"id":"2606.16354","title":"GraphBEV++: Multi-Modal Feature Alignment for Autonomous Driving","created":"2026-06-15","cited_by_count":0,"area":"driving"},{"id":"2607.10336","title":"PrismAD: Decoupled Planning via Semantic Mixture-of-Planners for End-to-End Autonomous Driving","created":"2026-07-11","cited_by_count":0,"area":"driving"},{"id":"2608.15573","title":"Not All History Helps: Velocity-Aware Selective Memory for Long-Horizon End-to-End Autonomous Driving","created":"2026-08-16","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":"2608.23405","title":"MomADv2: Reliable Temporal Memory for End-to-End Autonomous Driving","created":"2026-08-24","cited_by_count":0,"area":"driving"},{"id":"2608.24366","title":"Variance-Guided Spatial Attention Fusion for Robust End-to-End Driving under Asymmetric Sensor Degradation","created":"2026-08-25","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":"2609.02462","title":"VIPS: Vehicle-Infrastructure Cooperative Planning Benchmark via Pseudo-Simulation","created":"2026-09-02","cited_by_count":0,"area":"driving"},{"id":"2609.38862","title":"Efficient Multi-Modal Planning with Reward-Guided Preference Optimization for Autonomous Driving","created":"2026-09-30","cited_by_count":0,"area":"driving"},{"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":"2610.18030","title":"FlowSim: Rendering-Free Closed-Loop Simulation for Evaluating End-to-End Driving Systems","created":"2026-10-13","cited_by_count":0,"area":"driving"}],"next_cursor":null}