{"total":136,"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":"2205.15997","title":"TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving","created":"2022-05-31","cited_by_count":485,"area":"driving"},{"id":"2104.09224","title":"Multi-Modal Fusion Transformer for End-to-End Autonomous Driving","created":"2021-04-19","cited_by_count":377,"area":"driving"},{"id":"2207.07601","title":"ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learning","created":"2022-07-15","cited_by_count":368,"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":"2402.13243","title":"VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning","created":"2024-02-20","cited_by_count":289,"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":"2206.08129","title":"Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline","created":"2022-06-16","cited_by_count":248,"area":"driving"},{"id":"2410.23262","title":"EMMA: End-to-End Multimodal Model for Autonomous Driving","created":"2024-10-30","cited_by_count":231,"area":"driving"},{"id":"2108.08265","title":"End-to-End Urban Driving by Imitating a Reinforcement Learning Coach","created":"2021-08-18","cited_by_count":194,"area":"driving"},{"id":"2109.04456","title":"NEAT: Neural Attention Fields for End-to-End Autonomous Driving","created":"2021-09-09","cited_by_count":174,"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":"2210.07729","title":"Model-Based Imitation Learning for Urban Driving","created":"2022-10-14","cited_by_count":150,"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":"2203.11934","title":"Learning from All Vehicles","created":"2022-03-22","cited_by_count":135,"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":"2105.00636","title":"Learning to drive from a world on rails","created":"2021-05-03","cited_by_count":114,"area":"driving"},{"id":"2403.04133","title":"Towards learning-based planning:The nuPlan benchmark for real-world autonomous driving","created":"2024-03-07","cited_by_count":104,"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":"2204.13683","title":"KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients","created":"2022-04-28","cited_by_count":96,"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":"2205.02222","title":"COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehicles","created":"2022-05-04","cited_by_count":95,"area":"driving"},{"id":"2305.10507","title":"ReasonNet: End-to-End Driving with Temporal and Global Reasoning","created":"2023-05-17","cited_by_count":93,"area":"driving"},{"id":"2404.14327","title":"PLUTO: Pushing the Limit of Imitation Learning-based Planning for Autonomous Driving","created":"2024-04-22","cited_by_count":84,"area":"driving"},{"id":"2302.00673","title":"ADAPT: Action-aware Driving Caption Transformer","created":"2023-02-01","cited_by_count":78,"area":"driving"},{"id":"2111.08575","title":"GRI: General Reinforced Imitation and its Application to Vision-Based Autonomous Driving","created":"2021-11-16","cited_by_count":60,"area":"driving"},{"id":"2104.10753","title":"Multi-task Learning with Attention for End-to-end Autonomous Driving","created":"2021-04-21","cited_by_count":49,"area":"driving"},{"id":"2210.09539","title":"Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving","created":"2022-10-18","cited_by_count":44,"area":"driving"},{"id":"2405.15324","title":"Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving","created":"2024-05-24","cited_by_count":41,"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":"2409.06702","title":"Hint-AD: Holistically Aligned Interpretability in End-to-End Autonomous Driving","created":"2024-09-10","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":"2306.15713","title":"Rethinking Closed-loop Training for Autonomous Driving","created":"2023-06-27","cited_by_count":29,"area":"driving"},{"id":"2406.17680","title":"End-to-End Autonomous Driving without Costly Modularization and 3D Manual Annotation","created":"2024-06-25","cited_by_count":28,"area":"driving"},{"id":"2301.01006","title":"Policy Pre-training for Autonomous Driving via Self-supervised Geometric Modeling","created":"2023-01-03","cited_by_count":26,"area":"driving"},{"id":"2309.10443","title":"Rethinking Imitation-based Planner for Autonomous Driving","created":"2023-09-19","cited_by_count":25,"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":"2103.01882","title":"Exploring Imitation Learning for Autonomous Driving with Feedback Synthesizer and Differentiable Rasterization","created":"2021-03-02","cited_by_count":22,"area":"driving"},{"id":"2106.05966","title":"Learning by Watching","created":"2021-06-10","cited_by_count":22,"area":"driving"},{"id":"2204.05513","title":"End-to-end Autonomous Driving with Semantic Depth Cloud Mapping and Multi-agent","created":"2022-04-12","cited_by_count":21,"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":"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":"2502.18042","title":"VLM-E2E: Enhancing End-to-End Autonomous Driving with Multimodal Driver Attention Fusion","created":"2025-02-25","cited_by_count":20,"area":"driving"},{"id":"2109.06126","title":"Neural Network Guided Evolutionary Fuzzing for Finding Traffic Violations of Autonomous Vehicles","created":"2021-09-13","cited_by_count":19,"area":"driving"},{"id":"2204.10320","title":"SelfD: Self-Learning Large-Scale Driving Policies From the Web","created":"2022-04-21","cited_by_count":18,"area":"driving"},{"id":"2206.03004","title":"Driving in Real Life with Inverse Reinforcement Learning","created":"2022-06-07","cited_by_count":18,"area":"driving"},{"id":"2111.12137","title":"Learning Interactive Driving Policies via Data-driven Simulation","created":"2021-11-23","cited_by_count":17,"area":"driving"},{"id":"2207.00186","title":"MMFN: Multi-Modal-Fusion-Net for End-to-End Driving","created":"2022-07-01","cited_by_count":17,"area":"driving"},{"id":"2202.08557","title":"CADRE: A Cascade Deep Reinforcement Learning Framework for Vision-based Autonomous Urban Driving","created":"2022-02-17","cited_by_count":16,"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":"2505.15880","title":"Challenger: Affordable Adversarial Driving Video Generation","created":"2025-05-21","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":"2108.05030","title":"DQ-GAT: Towards Safe and Efficient Autonomous Driving with Deep Q-Learning and Graph Attention Networks","created":"2021-08-11","cited_by_count":13,"area":"driving"},{"id":"2404.04869","title":"Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs","created":"2024-04-07","cited_by_count":13,"area":"driving"},{"id":"2405.19687","title":"Autonomous Driving with Spiking Neural Networks","created":"2024-05-30","cited_by_count":13,"area":"driving"},{"id":"2302.04823","title":"Hierarchical Generative Adversarial Imitation Learning with Mid-level Input Generation for Autonomous Driving on Urban Environments","created":"2023-02-09","cited_by_count":12,"area":"driving"},{"id":"2503.08162","title":"FASIONAD++ : Integrating High-Level Instruction and Information Bottleneck in FAt-Slow fusION Systems for Enhanced Safety in Autonomous Driving with Adaptive Feedback","created":"2025-03-11","cited_by_count":12,"area":"driving"},{"id":"2403.01238","title":"On the Road to Portability: Compressing End-to-End Motion Planner for Autonomous Driving","created":"2024-03-02","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":"2302.03198","title":"Scaling Vision-based End-to-End Driving with Multi-View Attention Learning","created":"2023-02-07","cited_by_count":8,"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":"2112.03908","title":"Causal Imitative Model for Autonomous Driving","created":"2021-12-07","cited_by_count":7,"area":"driving"},{"id":"2311.18636","title":"End-to-end Autonomous Driving using Deep Learning: A Systematic Review","created":"2023-08-27","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":"2407.06546","title":"Exploring the Causality of End-to-End Autonomous Driving","created":"2024-07-09","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":"2211.11579","title":"Dynamic Conditional Imitation Learning for Autonomous Driving","created":"2022-11-17","cited_by_count":6,"area":"driving"},{"id":"2305.19904","title":"Efficient Learning of Urban Driving Policies Using Bird's-Eye-View State Representations","created":"2023-05-31","cited_by_count":6,"area":"driving"},{"id":"2403.18965","title":"LORD: Large Models based Opposite Reward Design for Autonomous Driving","created":"2024-03-27","cited_by_count":6,"area":"driving"},{"id":"2405.04491","title":"TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters","created":"2024-05-07","cited_by_count":6,"area":"driving"},{"id":"2110.11573","title":"A Versatile and Efficient Reinforcement Learning Framework for Autonomous Driving","created":"2021-10-22","cited_by_count":5,"area":"driving"},{"id":"2405.00316","title":"Enhance Planning with Physics-informed Safety Controller for End-to-end Autonomous Driving","created":"2024-05-01","cited_by_count":5,"area":"driving"},{"id":"2110.08586","title":"Generative Adversarial Imitation Learning for End-to-End Autonomous Driving on Urban Environments","created":"2021-10-16","cited_by_count":4,"area":"driving"},{"id":"2210.03772","title":"Traffic-Aware Autonomous Driving with Differentiable Traffic Simulation","created":"2022-10-07","cited_by_count":4,"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":"2409.14165","title":"A Survey on Large Language Model-empowered Autonomous Driving","created":"2024-09-21","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":"2212.08729","title":"Distribution-aware Goal Prediction and Conformant Model-based Planning for Safe Autonomous Driving","created":"2022-12-16","cited_by_count":3,"area":"driving"},{"id":"2310.20650","title":"Addressing Limitations of State-Aware Imitation Learning for Autonomous Driving","created":"2023-10-31","cited_by_count":3,"area":"driving"},{"id":"2405.07573","title":"MaskFuser: Masked Fusion of Joint Multi-Modal Tokenization for End-to-End Autonomous Driving","created":"2024-05-13","cited_by_count":3,"area":"driving"},{"id":"2411.04653","title":"IGDrivSim: A Benchmark for the Imitation Gap in Autonomous Driving","created":"2024-11-07","cited_by_count":3,"area":"driving"},{"id":"2511.11740","title":"ExpertAD: Enhancing Autonomous Driving Systems with Mixture of Experts","created":"2025-11-13","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":"2606.17386","title":"TerraTransfer: Learning End-to-End Driving Policies Without Expert Demonstrations","created":"2026-06-16","cited_by_count":3,"area":"driving"},{"id":"2101.05970","title":"Affordance-based Reinforcement Learning for Urban Driving","created":"2021-01-15","cited_by_count":2,"area":"driving"},{"id":"2206.00608","title":"On the Choice of Data for Efficient Training and Validation of End-to-End Driving Models","created":"2022-06-01","cited_by_count":2,"area":"driving"},{"id":"2206.10249","title":"Incorporating Voice Instructions in Model-Based Reinforcement Learning for Self-Driving Cars","created":"2022-06-21","cited_by_count":2,"area":"driving"},{"id":"2210.16567","title":"DeFIX: Detecting and Fixing Failure Scenarios with Reinforcement Learning in Imitation Learning Based Autonomous Driving","created":"2022-10-29","cited_by_count":2,"area":"driving"},{"id":"2303.11888","title":"Penalty-Based Imitation Learning With Cross Semantics Generation Sensor Fusion for Autonomous Driving","created":"2023-03-21","cited_by_count":2,"area":"driving"},{"id":"2308.01180","title":"Interpretable End-to-End Driving Model for Implicit Scene Understanding","created":"2023-08-02","cited_by_count":2,"area":"driving"},{"id":"2308.01496","title":"Target-point Attention Transformer: A novel trajectory predict network for end-to-end autonomous driving","created":"2023-08-03","cited_by_count":2,"area":"driving"},{"id":"2309.07808","title":"What Matters to Enhance Traffic Rule Compliance of Imitation Learning for End-to-End Autonomous Driving","created":"2023-09-14","cited_by_count":2,"area":"driving"},{"id":"2310.14224","title":"Detrive: Imitation Learning with Transformer Detection for End-to-End Autonomous Driving","created":"2023-10-22","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":"2607.26005","title":"Pictura: Perspective-View Self-Play at Scale for Driving","created":"2026-07-28","cited_by_count":2,"area":"driving"},{"id":"2105.10014","title":"Evaluating Robustness over High Level Driving Instruction for Autonomous Driving","created":"2021-05-20","cited_by_count":1,"area":"driving"}],"next_cursor":"100"}