{"total":46,"rows":[{"id":"2508.11428","title":"ImagiDrive: A Unified Imagination-and-Planning Framework for Autonomous Driving","created":"2025-08-15","cited_by_count":25,"area":"driving"},{"id":"2604.08535","title":"Fail2Drive: Benchmarking Closed-Loop Driving Generalization","created":"2026-04-09","cited_by_count":17,"area":"driving"},{"id":"2603.06049","title":"Devil is in Narrow Policy: Unleashing Exploration in Driving VLA Models","created":"2026-03-06","cited_by_count":15,"area":"driving"},{"id":"2604.00813","title":"DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale","created":"2026-04-01","cited_by_count":13,"area":"driving"},{"id":"2506.11234","title":"Poutine: Vision-Language-Trajectory Pre-Training and Reinforcement Learning Post-Training Enable Robust End-to-End Autonomous Driving","created":"2025-06-12","cited_by_count":11,"area":"driving"},{"id":"2512.09864","title":"UniUGP: Unifying Understanding, Generation, and Planing For End-to-end Autonomous Driving","created":"2025-12-10","cited_by_count":10,"area":"driving"},{"id":"2605.31572","title":"nuReasoning: A Reasoning-Centric Dataset and Benchmark for Long-Tail Autonomous Driving","created":"2026-05-29","cited_by_count":9,"area":"driving"},{"id":"2506.10145","title":"RoCA: Robust Cross-Domain End-to-End Autonomous Driving","created":"2025-06-11","cited_by_count":8,"area":"driving"},{"id":"2511.07292","title":"PlanT 2.0: Exposing Biases and Structural Flaws in Closed-Loop Driving","created":"2025-11-10","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":"2505.08854","title":"Generative AI for Autonomous Driving: Frontiers and Opportunities","created":"2025-05-13","cited_by_count":7,"area":"driving"},{"id":"2602.15891","title":"Learning to Drive in New Cities Without Human Demonstrations","created":"2026-02-09","cited_by_count":7,"area":"driving"},{"id":"2603.18561","title":"CausalVAD: De-confounding End-to-End Autonomous Driving via Causal Intervention","created":"2026-03-19","cited_by_count":7,"area":"driving"},{"id":"2603.15185","title":"What Matters for Scalable and Robust Learning in End-to-End Driving Planners?","created":"2026-03-16","cited_by_count":5,"area":"driving"},{"id":"2603.25740","title":"Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Driving","created":"2026-03-26","cited_by_count":5,"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":"2506.14589","title":"NetRoller: Interfacing General and Specialized Models for End-to-End Autonomous Driving","created":"2025-06-17","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":"2512.00021","title":"Foundation Models for Trajectory Planning in Autonomous Driving: A Review of Progress and Open Challenges","created":"2025-10-31","cited_by_count":3,"area":"driving"},{"id":"2605.18059","title":"Bench2Drive-Robust: Benchmarking Closed-Loop Autonomous Driving under Deployment Perturbations","created":"2026-05-18","cited_by_count":3,"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":"2603.14354","title":"Deconfounded Lifelong Learning for Autonomous Driving via Dynamic Knowledge Spaces","created":"2026-03-15","cited_by_count":2,"area":"driving"},{"id":"2603.25672","title":"Can Users Specify Driving Speed? Bench2Drive-Speed: Benchmark and Baselines for Desired-Speed Conditioned Autonomous Driving","created":"2026-03-26","cited_by_count":2,"area":"driving"},{"id":"2604.12656","title":"FeaXDrive: Feasibility-aware Trajectory-Centric Diffusion Planning for End-to-End Autonomous Driving","created":"2026-04-14","cited_by_count":2,"area":"driving"},{"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":"2605.19524","title":"SafeAlign-VLA: A Negative-Enhanced Safe Alignment Framework for Risk-Aware Autonomous Driving","created":"2026-05-19","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":"2601.01762","title":"AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving","created":"2026-01-05","cited_by_count":1,"area":"driving"},{"id":"2605.09972","title":"HiDrive: A Closed-Loop Benchmark for High-Level Autonomous Driving","created":"2026-05-11","cited_by_count":1,"area":"driving"},{"id":"2512.12302","title":"From Human Intention to Action Prediction: Intention-Driven End-to-End Autonomous Driving","created":"2025-12-13","cited_by_count":0,"area":"driving"},{"id":"2604.07378","title":"Evaluation as Evolution: Transforming Adversarial Diffusion into Closed-Loop Curricula for Autonomous Vehicles","created":"2026-04-08","cited_by_count":0,"area":"driving"},{"id":"2604.24562","title":"Towards Lawful Autonomous Driving: Deriving Scenario-Aware Driving Requirements from Traffic Laws and Regulations","created":"2026-04-27","cited_by_count":0,"area":"driving"},{"id":"2605.10386","title":"GuardAD: Safeguarding Autonomous Driving MLLMs via Markovian Safety Logic","created":"2026-05-11","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":"2605.22504","title":"LACO: Adaptive Latent Communication for Collaborative Driving","created":"2026-05-21","cited_by_count":0,"area":"driving"},{"id":"2606.12236","title":"DrivingAgent: Design and Scheduling Agents for Autonomous Driving Systems","created":"2026-06-10","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":"2608.18035","title":"Plug-and-Play Traffic Element Awareness for End-to-End Autonomous Driving","created":"2026-08-18","cited_by_count":0,"area":"driving"},{"id":"2608.24525","title":"RoG-DAgger: Rollout-Guided Post-Training for End-to-End Driving","created":"2026-08-25","cited_by_count":0,"area":"driving"},{"id":"2608.28656","title":"RedLight-VLA: Models for traffic-rule grounding and behavioral emphasis in driving policies","created":"2026-08-21","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":"2609.08217","title":"Drive by Hindsight and Foresight: Tool-Grounded Synergistic Reasoning over Hierarchical Memory for Autonomous Driving","created":"2026-09-08","cited_by_count":0,"area":"driving"},{"id":"2609.31814","title":"DriveHierarchy: A Benchmark for Diagnosing VLM Driving Capabilities from Open-Loop Understanding to Closed-Loop Execution","created":"2026-09-25","cited_by_count":0,"area":"driving"},{"id":"2609.33190","title":"FocusDrive: Reasoning with Visual Focus for Autonomous Driving","created":"2026-09-27","cited_by_count":0,"area":"driving"},{"id":"2610.00926","title":"A Survey on End-to-End Autonomous Driving Training from the Perspectives of Data, Strategy, and Platform","created":"2026-10-01","cited_by_count":0,"area":"driving"}],"next_cursor":null}