{"total":93,"rows":[{"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":"2312.07488","title":"LMDrive: Closed-Loop End-to-End Driving with Large Language Models","created":"2023-12-12","cited_by_count":305,"area":"driving"},{"id":"2506.13757","title":"AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning","created":"2025-06-16","cited_by_count":260,"area":"lr"},{"id":"2312.09245","title":"DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving","created":"2023-12-14","cited_by_count":233,"area":"mllm"},{"id":"2406.08481","title":"Enhancing End-to-End Autonomous Driving with Latent World Model","created":"2024-06-12","cited_by_count":166,"area":"wm"},{"id":"2503.09594","title":"SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignment","created":"2025-03-12","cited_by_count":150,"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":"2506.06659","title":"DriveSuprim: Towards Precise Trajectory Selection for End-to-End Planning","created":"2025-06-07","cited_by_count":94,"area":null},{"id":"2412.14446","title":"VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision","created":"2024-12-19","cited_by_count":86,"area":"lr"},{"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":"2403.16996","title":"DriveCoT: Integrating Chain-of-Thought Reasoning with End-to-End Driving","created":"2024-03-25","cited_by_count":67,"area":"lr"},{"id":"2505.23757","title":"Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models","created":"2025-05-29","cited_by_count":60,"area":"vla"},{"id":"2406.10165","title":"CarLLaVA: Vision language models for camera-only closed-loop driving","created":"2024-06-14","cited_by_count":57,"area":"mllm"},{"id":"2408.09251","title":"V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models","created":"2024-08-17","cited_by_count":47,"area":"mllm"},{"id":"2505.16394","title":"Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)","created":"2025-05-22","cited_by_count":47,"area":"wm"},{"id":"2312.04372","title":"LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs","created":"2023-12-07","cited_by_count":45,"area":"driving"},{"id":"2407.02797","title":"Solving Motion Planning Tasks with a Scalable Generative Model","created":"2024-07-03","cited_by_count":40,"area":null},{"id":"2404.07569","title":"Can Vehicle Motion Planning Generalize to Realistic Long-tail Scenarios?","created":"2024-04-11","cited_by_count":38,"area":null},{"id":"2403.11492","title":"SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Prediction","created":"2024-03-18","cited_by_count":34,"area":null},{"id":"2503.03074","title":"BEVDriver: Leveraging BEV Maps in LLMs for Robust Closed-Loop Driving","created":"2025-03-05","cited_by_count":26,"area":"driving"},{"id":"2312.03408","title":"Open-sourced Data Ecosystem in Autonomous Driving: the Present and Future","created":"2023-12-06","cited_by_count":23,"area":null},{"id":"2405.05885","title":"VLM-Auto: VLM-based Autonomous Driving Assistant with Human-like Behavior and Understanding for Complex Road Scenes","created":"2024-05-09","cited_by_count":23,"area":"driving"},{"id":"2512.20563","title":"LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving","created":"2025-12-23","cited_by_count":23,"area":"driving"},{"id":"2409.16663","title":"Mitigating Covariate Shift in Imitation Learning for Autonomous Vehicles Using Latent Space Generative World Models","created":"2024-09-25","cited_by_count":22,"area":"wm"},{"id":"2505.20024","title":"ReasonPlan: Unified Scene Prediction and Decision Reasoning for Closed-loop Autonomous Driving","created":"2025-05-26","cited_by_count":22,"area":"lr"},{"id":"2601.01528","title":"DrivingGen: A Comprehensive Benchmark for Generative Video World Models in Autonomous Driving","created":"2026-01-04","cited_by_count":21,"area":"wm"},{"id":"2404.09496","title":"Towards Collaborative Autonomous Driving: Simulation Platform and End-to-End System","created":"2024-04-15","cited_by_count":20,"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":"2311.17948","title":"Action-slot: Visual Action-centric Representations for Multi-label Atomic Activity Recognition in Traffic Scenes","created":"2023-11-29","cited_by_count":12,"area":null},{"id":"2312.01659","title":"RiskBench: A Scenario-based Benchmark for Risk Identification","created":"2023-12-04","cited_by_count":12,"area":null},{"id":"2503.18108","title":"Unraveling the Effects of Synthetic Data on End-to-End Autonomous Driving","created":"2025-03-23","cited_by_count":12,"area":"wm"},{"id":"2410.05051","title":"ComDrive: Comfort-Oriented End-to-End Autonomous Driving","created":"2024-10-07","cited_by_count":11,"area":"diffusion"},{"id":"2508.21824","title":"DriveQA: Passing the Driving Knowledge Test","created":"2025-08-29","cited_by_count":10,"area":"driving"},{"id":"2511.06253","title":"AdaDrive: Self-Adaptive Slow-Fast System for Language-Grounded Autonomous Driving","created":"2025-11-09","cited_by_count":10,"area":"driving"},{"id":"2410.18238","title":"CARLA2Real: a tool for reducing the sim2real appearance gap in CARLA simulator","created":"2024-10-23","cited_by_count":9,"area":null},{"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":"2512.17370","title":"TakeAD: Preference-based Post-optimization for End-to-end Autonomous Driving with Expert Takeover Data","created":"2025-12-19","cited_by_count":8,"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":"2410.08669","title":"SmartPretrain: Model-Agnostic and Dataset-Agnostic Representation Learning for Motion Prediction","created":"2024-10-11","cited_by_count":7,"area":null},{"id":"2511.19914","title":"CoC-VLA: Delving into Adversarial Domain Transfer for Explainable Autonomous Driving via Chain-of-Causality Visual-Language-Action Model","created":"2025-11-25","cited_by_count":7,"area":"driving"},{"id":"2402.12666","title":"Pre-trained Transformer-Enabled Strategies with Human-Guided Fine-Tuning for End-to-end Navigation of Autonomous Vehicles","created":"2024-02-20","cited_by_count":6,"area":"driving"},{"id":"2409.18053","title":"DualAD: Dual-Layer Planning for Reasoning in Autonomous Driving","created":"2024-09-26","cited_by_count":6,"area":"lr"},{"id":"2504.12667","title":"Fully Unified Motion Planning for End-to-End Autonomous Driving","created":"2025-04-17","cited_by_count":6,"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":"2507.05754","title":"LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving","created":"2025-07-08","cited_by_count":5,"area":"driving"},{"id":"2508.07089","title":"ForeSight: Multi-View Streaming Joint Object Detection and Trajectory Forecasting","created":"2025-08-09","cited_by_count":5,"area":null},{"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":"2508.18898","title":"Interpretable Decision-Making for End-to-End Autonomous Driving","created":"2025-08-26","cited_by_count":4,"area":"driving"},{"id":"2509.16950","title":"Temporal Logic-Based Multi-Vehicle Backdoor Attacks against Offline RL Agents in End-to-end Autonomous Driving","created":"2025-09-21","cited_by_count":4,"area":"safety"},{"id":"2601.03460","title":"FROST-Drive: Scalable and Efficient End-to-End Driving with a Frozen Vision Encoder","created":"2026-01-06","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":"2505.05223","title":"Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving","created":"2025-05-08","cited_by_count":3,"area":"driving"},{"id":"2505.05515","title":"Nature's Insight: A Novel Framework and Comprehensive Analysis of Agentic Reasoning Through the Lens of Neuroscience","created":"2025-05-07","cited_by_count":3,"area":"agents"},{"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":"2506.00819","title":"DriveMind: A Dual Visual Language Model-based Reinforcement Learning Framework for Autonomous Driving","created":"2025-06-01","cited_by_count":3,"area":"mllm"},{"id":"2511.11740","title":"ExpertAD: Enhancing Autonomous Driving Systems with Mixture of Experts","created":"2025-11-13","cited_by_count":3,"area":"driving"},{"id":"2602.11656","title":"SToRM: Supervised Token Reduction for Multi-modal LLMs toward efficient end-to-end autonomous driving","created":"2026-02-12","cited_by_count":3,"area":"mllm"},{"id":"2603.25968","title":"Neuro-Cognitive Reward Modeling for Human-Centered Autonomous Vehicle Control","created":"2026-03-26","cited_by_count":3,"area":"driving"},{"id":"2409.01178","title":"Integrating End-to-End and Modular Driving Approaches for Online Corner Case Detection in Autonomous Driving","created":"2024-09-02","cited_by_count":2,"area":"driving"},{"id":"2409.17605","title":"Good Data Is All Imitation Learning Needs","created":"2024-09-26","cited_by_count":2,"area":"offlinerl"},{"id":"2410.02253","title":"From Imitation to Exploration: End-to-end Autonomous Driving based on World Model","created":"2024-10-03","cited_by_count":2,"area":"wm"},{"id":"2504.05950","title":"AEGIS: Human Attention-based Explainable Guidance for Intelligent Vehicle Systems","created":"2025-04-08","cited_by_count":2,"area":null},{"id":"2509.20938","title":"Autoregressive End-to-End Planning with Time-Invariant Spatial Alignment and Multi-Objective Policy Refinement","created":"2025-09-25","cited_by_count":2,"area":"alignment"},{"id":"2602.09018","title":"Robustness Is a Function, Not a Number: A Factorized Comprehensive Study of OOD Robustness in Vision-Based Driving","created":"2026-02-09","cited_by_count":2,"area":"driving"},{"id":"2604.08719","title":"LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving","created":"2026-04-09","cited_by_count":2,"area":"wm"},{"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":"2402.15650","title":"Uniformly Safe RL with Objective Suppression for Multi-Constraint Safety-Critical Applications","created":"2024-02-23","cited_by_count":1,"area":"deeprl"},{"id":"2509.02966","title":"KEPT: Knowledge-Enhanced Prediction of Trajectories from Consecutive Driving Frames with Vision-Language Models","created":"2025-09-03","cited_by_count":1,"area":"mllm"},{"id":"2602.23259","title":"Risk-Aware World Model Predictive Control for Generalizable End-to-End Autonomous Driving","created":"2026-02-26","cited_by_count":1,"area":"wm"},{"id":"2603.14908","title":"PerlAD: Towards Enhanced Closed-loop End-to-end Autonomous Driving with Pseudo-simulation-based Reinforcement Learning","created":"2026-03-16","cited_by_count":1,"area":"driving"},{"id":"2607.15621","title":"Think at 5 Hz, Act at 20 Hz: Asynchronous Fast-Slow Vision-Language-Action Inference for Closed-Loop Driving","created":"2026-07-17","cited_by_count":1,"area":"lr"},{"id":"2402.05064","title":"Tuning the feedback controller gains is a simple way to improve autonomous driving performance","created":"2024-02-07","cited_by_count":0,"area":"driving"},{"id":"2402.19059","title":"WHU-Synthetic: A Synthetic Perception Dataset for 3-D Multitask Model Research","created":"2024-02-29","cited_by_count":0,"area":null},{"id":"2406.08421","title":"PRIBOOT: A New Data-Driven Expert for Improved Driving Simulations","created":"2024-06-12","cited_by_count":0,"area":null},{"id":"2407.02878","title":"Efficient Fusion and Task Guided Embedding for End-to-end Autonomous Driving","created":"2024-07-03","cited_by_count":0,"area":"driving"},{"id":"2409.14170","title":"LFP: Efficient and Accurate End-to-End Lane-Level Planning via Camera-LiDAR Fusion","created":"2024-09-21","cited_by_count":0,"area":null},{"id":"2410.16197","title":"LASER: Script Execution by Autonomous Agents for On-demand Traffic Simulation","created":"2024-10-21","cited_by_count":0,"area":"agents"},{"id":"2411.07711","title":"OWLed: Outlier-weighed Layerwise Pruning for Efficient Autonomous Driving Framework","created":"2024-11-12","cited_by_count":0,"area":"driving"},{"id":"2506.23523","title":"Lightweight Temporal Transformer Decomposition for Federated Autonomous Driving","created":"2025-06-30","cited_by_count":0,"area":null},{"id":"2508.20762","title":"SKGE-SWIN: End-To-End Autonomous Vehicle Waypoint Prediction and Navigation Using Skip Stage Swin Transformer","created":"2025-08-28","cited_by_count":0,"area":"driving"},{"id":"2602.10160","title":"AD$^2$: Analysis and Detection of Adversarial Threats in Visual Perception for End-to-End Autonomous Driving Systems","created":"2026-02-10","cited_by_count":0,"area":"driving"},{"id":"2603.23919","title":"Uncertainty-Aware Vision-based Risk Object Identification via Conformal Risk Tube Prediction","created":"2026-03-25","cited_by_count":0,"area":null},{"id":"2605.04355","title":"InterFuserDVS: Event-Enhanced Sensor Fusion for Safe RL-Based Decision Making","created":"2026-05-05","cited_by_count":0,"area":null},{"id":"2607.04812","title":"TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving","created":"2026-07-06","cited_by_count":0,"area":"driving"},{"id":"2607.09138","title":"BeyondSight: Object Permanence for End-to-End Autonomous Driving","created":"2026-07-10","cited_by_count":0,"area":"driving"},{"id":"2607.29052","title":"Outcome-Guided Distillation: A Teacher-Student Framework to Advance VLM Reasoning in Autonomous Driving","created":"2026-07-31","cited_by_count":0,"area":"lr"},{"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":"2609.04807","title":"CoLMIN: LLM-based Multi-Decision Path Negotiation for Cooperative Autonomous Driving","created":"2026-09-04","cited_by_count":0,"area":null},{"id":"2609.38641","title":"Vision-Language-Action Autonomous Driving Agent with Language-based Memory","created":"2026-09-29","cited_by_count":0,"area":"mllm"}],"next_cursor":null}