{"total":55,"rows":[{"id":"2303.12077","title":"VAD: Vectorized Scene Representation for Efficient Autonomous Driving","created":"2023-03-21","cited_by_count":622,"area":"driving"},{"id":"2306.16927","title":"End-to-end Autonomous Driving: Challenges and Frontiers","created":"2023-06-29","cited_by_count":490,"area":"driving"},{"id":"2406.15349","title":"NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking","created":"2024-06-21","cited_by_count":354,"area":"driving"},{"id":"2406.03877","title":"Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving","created":"2024-06-06","cited_by_count":252,"area":"driving"},{"id":"2310.01957","title":"Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving","created":"2023-10-03","cited_by_count":232,"area":"driving"},{"id":"2305.06242","title":"Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving","created":"2023-05-10","cited_by_count":169,"area":"driving"},{"id":"2506.04218","title":"Pseudo-Simulation for Autonomous Driving","created":"2025-06-04","cited_by_count":150,"area":"driving"},{"id":"2308.00398","title":"DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving","created":"2023-08-01","cited_by_count":144,"area":"driving"},{"id":"2503.07656","title":"DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving","created":"2025-03-07","cited_by_count":126,"area":"driving"},{"id":"2307.04370","title":"Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Survey","created":"2023-07-10","cited_by_count":103,"area":"driving"},{"id":"2306.07957","title":"Hidden Biases of End-to-End Driving Models","created":"2023-06-13","cited_by_count":96,"area":"driving"},{"id":"2406.14556","title":"Asynchronous Large Language Model Enhanced Planner for Autonomous Driving","created":"2024-06-20","cited_by_count":38,"area":"driving"},{"id":"2502.19908","title":"CarPlanner: Consistent Auto-regressive Trajectory Planning for Large-scale Reinforcement Learning in Autonomous Driving","created":"2025-02-27","cited_by_count":34,"area":"driving"},{"id":"2311.08100","title":"PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Driving","created":"2023-11-14","cited_by_count":33,"area":"driving"},{"id":"2412.09602","title":"Hidden Biases of End-to-End Driving Datasets","created":"2024-12-12","cited_by_count":30,"area":"driving"},{"id":"2309.10443","title":"Rethinking Imitation-based Planner for Autonomous Driving","created":"2023-09-19","cited_by_count":25,"area":"driving"},{"id":"2410.15774","title":"Generalizing Motion Planners with Mixture of Experts for Autonomous Driving","created":"2024-10-21","cited_by_count":22,"area":"driving"},{"id":"2402.02426","title":"Hybrid-Prediction Integrated Planning for Autonomous Driving","created":"2024-02-04","cited_by_count":18,"area":"driving"},{"id":"2311.10747","title":"Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving","created":"2023-10-31","cited_by_count":17,"area":"driving"},{"id":"2403.02877","title":"ActiveAD: Planning-Oriented Active Learning for End-to-End Autonomous Driving","created":"2024-03-05","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":"2308.12779","title":"On Offline Evaluation of 3D Object Detection for Autonomous Driving","created":"2023-08-24","cited_by_count":11,"area":"driving"},{"id":"2404.01486","title":"QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Driving","created":"2024-04-01","cited_by_count":11,"area":"driving"},{"id":"2508.21824","title":"DriveQA: Passing the Driving Knowledge Test","created":"2025-08-29","cited_by_count":10,"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":"2407.15843","title":"CarFormer: Self-Driving with Learned Object-Centric Representations","created":"2024-07-22","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":"2403.12176","title":"Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving","created":"2024-03-18","cited_by_count":7,"area":"driving"},{"id":"2403.12552","title":"M2DA: Multi-Modal Fusion Transformer Incorporating Driver Attention for Autonomous Driving","created":"2024-03-19","cited_by_count":7,"area":"driving"},{"id":"2303.13986","title":"Interpretable Motion Planner for Urban Driving via Hierarchical Imitation Learning","created":"2023-03-24","cited_by_count":4,"area":"driving"},{"id":"2508.18898","title":"Interpretable Decision-Making for End-to-End Autonomous Driving","created":"2025-08-26","cited_by_count":4,"area":"driving"},{"id":"2510.15505","title":"Perfect Prediction or Plenty of Proposals? What Matters Most in Planning for Autonomous Driving","created":"2025-10-17","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":"2605.18059","title":"Bench2Drive-Robust: Benchmarking Closed-Loop Autonomous Driving under Deployment Perturbations","created":"2026-05-18","cited_by_count":3,"area":"driving"},{"id":"2409.12667","title":"METDrive: Multi-modal End-to-end Autonomous Driving with Temporal Guidance","created":"2024-09-19","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":"2603.15771","title":"CorrectionPlanner: Self-Correction Planner with Reinforcement Learning in Autonomous Driving","created":"2026-03-16","cited_by_count":2,"area":"driving"},{"id":"2605.06264","title":"Can Attribution Predict Risk? From Multi-View Attribution to Planning Risk Signals in End-to-End Autonomous Driving","created":"2026-05-07","cited_by_count":2,"area":"driving"},{"id":"2406.08349","title":"Utilizing Navigation Paths to Generate Target Points for Enhanced End-to-End Autonomous Driving Planning","created":"2024-06-12","cited_by_count":1,"area":"driving"},{"id":"2406.08855","title":"Trajectory Planning for Autonomous Driving in Unstructured Scenarios Based on Graph Neural Network and Numerical Optimization","created":"2024-06-13","cited_by_count":1,"area":"driving"},{"id":"2411.07719","title":"EMPERROR: A Flexible Generative Perception Error Model for Probing Self-Driving Planners","created":"2024-11-12","cited_by_count":1,"area":"driving"},{"id":"2504.06584","title":"CAFE-AD: Cross-Scenario Adaptive Feature Enhancement for Trajectory Planning in Autonomous Driving","created":"2025-04-09","cited_by_count":1,"area":"driving"},{"id":"2506.23960","title":"ADReFT: Adaptive Decision Repair for Safe Autonomous Driving via Reinforcement Fine-Tuning","created":"2025-06-30","cited_by_count":1,"area":"driving"},{"id":"2512.03936","title":"Driving is a Game: Combining Planning and Prediction with Bayesian Iterative Best Response","created":"2025-12-03","cited_by_count":1,"area":"driving"},{"id":"2601.09377","title":"ReflexDiffusion: Reflection-Enhanced Trajectory Planning for High-lateral-acceleration Scenarios in Autonomous Driving","created":"2026-01-14","cited_by_count":1,"area":"driving"},{"id":"2602.23499","title":"TaCarla: A comprehensive benchmarking dataset for end-to-end autonomous driving","created":"2026-02-26","cited_by_count":1,"area":"driving"},{"id":"2403.07232","title":"Tractable Joint Prediction and Planning over Discrete Behavior Modes for Urban Driving","created":"2024-03-12","cited_by_count":0,"area":"driving"},{"id":"2410.22752","title":"SoftCTRL: Soft conservative KL-control of Transformer Reinforcement Learning for Autonomous Driving","created":"2024-10-30","cited_by_count":0,"area":"driving"},{"id":"2506.23995","title":"STCLocker: Deadlock Avoidance Testing for Autonomous Driving Systems","created":"2025-06-30","cited_by_count":0,"area":"driving"},{"id":"2606.10688","title":"Self-Supervised Relevance Modelling in Autonomous Driving via Counterfactual Analysis","created":"2026-06-09","cited_by_count":0,"area":"driving"},{"id":"2607.04331","title":"Agent-driven Long-tail Simulation for Autonomous Driving","created":"2026-07-05","cited_by_count":0,"area":"driving"},{"id":"2607.10438","title":"Large Language Model Enhanced Differentiable Trajectory Planning for IoT-Enabled Autonomous Driving","created":"2026-07-11","cited_by_count":0,"area":"driving"},{"id":"2608.12198","title":"Learning-Based Behavior Planning for Automated Driving: Real-World Integration and Deployment","created":"2026-08-12","cited_by_count":0,"area":"driving"},{"id":"2609.31137","title":"INTERACT: Interactive Planning for Autonomous Driving via Anchor-Conditioned Prediction and Trust-Region Refinement","created":"2026-09-25","cited_by_count":0,"area":"driving"},{"id":"2609.39995","title":"Learning to Explain While Planning: Rule-Aligned Diffusion Planning for Autonomous Driving","created":"2026-09-30","cited_by_count":0,"area":"driving"}],"next_cursor":null}