{"total":49,"rows":[{"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":"2506.04218","title":"Pseudo-Simulation for Autonomous Driving","created":"2025-06-04","cited_by_count":150,"area":"driving"},{"id":"2503.12820","title":"Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillation","created":"2025-03-17","cited_by_count":96,"area":"driving"},{"id":"2404.07762","title":"NeuroNCAP: Photorealistic Closed-loop Safety Testing for Autonomous Driving","created":"2024-04-11","cited_by_count":62,"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":"2506.11526","title":"Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysis","created":"2025-06-13","cited_by_count":38,"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":"2512.20563","title":"LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving","created":"2025-12-23","cited_by_count":23,"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":"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":"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":"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":"2606.19836","title":"World Engine: Towards the Era of Post-Training for Autonomous Driving","created":"2026-06-18","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":"2605.00066","title":"Do Open-Loop Metrics Predict Closed-Loop Driving? A Cross-Benchmark Correlation Study of NAVSIM and Bench2Drive","created":"2026-04-30","cited_by_count":6,"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":"2605.10034","title":"Beyond Self-Play and Scale: A Behavior Benchmark for Generalization in Autonomous Driving","created":"2026-05-11","cited_by_count":5,"area":"driving"},{"id":"2410.09681","title":"LoRD: Adapting Differentiable Driving Policies to Distribution Shifts","created":"2024-10-13","cited_by_count":4,"area":"driving"},{"id":"2509.17080","title":"CoPlanner: An Interactive Motion Planner with Contingency-Aware Diffusion for Autonomous Driving","created":"2025-09-21","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":"2409.14196","title":"Adversarial and Reactive Traffic Entities for Behavior-Realistic Driving Simulation: A Review","created":"2024-09-21","cited_by_count":3,"area":"driving"},{"id":"2503.08388","title":"V-Max: A Reinforcement Learning Framework for Autonomous Driving","created":"2025-03-11","cited_by_count":3,"area":"driving"},{"id":"2605.08084","title":"123D: Unifying Multi-Modal Autonomous Driving Data at Scale","created":"2026-05-08","cited_by_count":3,"area":"driving"},{"id":"2609.06055","title":"DriveZero: End-to-End Driving Beyond Human Demonstrations","created":"2026-09-05","cited_by_count":3,"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":"2606.31830","title":"PriorEye: Geospatial Visual Priors for End-to-End Autonomous Driving","created":"2026-06-30","cited_by_count":2,"area":"driving"},{"id":"2409.02871","title":"Hybrid Imitation-Learning Motion Planner for Urban Driving","created":"2024-09-04","cited_by_count":1,"area":"driving"},{"id":"2411.18714","title":"Explainable deep learning improves human mental models of self-driving cars","created":"2024-11-27","cited_by_count":1,"area":"driving"},{"id":"2502.11352","title":"A Framework for Learning Scoring Rules in Autonomous Driving Planning Systems","created":"2025-02-17","cited_by_count":1,"area":"driving"},{"id":"2503.19713","title":"Semi-SMD: Semi-Supervised Metric Depth Estimation via Surrounding Cameras for Autonomous Driving","created":"2025-03-25","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":"2602.07339","title":"RAPiD: Reward-Guided Consistency Distillation of Diffusion Planners for Real-Time Autonomous Driving","created":"2026-02-07","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":"2603.01023","title":"An Open-Source Modular Benchmark for Diffusion-Based Motion Planning in Closed-Loop Autonomous Driving","created":"2026-03-01","cited_by_count":1,"area":"driving"},{"id":"2604.08366","title":"Scaling-Aware Data Selection for End-to-End Autonomous Driving Systems","created":"2026-04-09","cited_by_count":1,"area":"driving"},{"id":"2606.30537","title":"Learning from Mistakes: Rollout-Retrieval Lifelong Policy Learning for Autonomous Driving","created":"2026-06-29","cited_by_count":1,"area":"driving"},{"id":"2410.15607","title":"Reinforced Imitative Trajectory Planning for Urban Automated Driving","created":"2024-10-21","cited_by_count":0,"area":"driving"},{"id":"2509.13579","title":"TreeIRL: Safe Urban Driving with Tree Search and Inverse Reinforcement Learning","created":"2025-09-16","cited_by_count":0,"area":"driving"},{"id":"2602.12563","title":"The Constant Eye: Benchmarking and Bridging Appearance Robustness in Autonomous Driving","created":"2026-02-13","cited_by_count":0,"area":"driving"},{"id":"2604.08031","title":"Open-Ended Instruction Realization with LLM-Enabled Multi-Planner Scheduling in Autonomous Vehicles","created":"2026-04-09","cited_by_count":0,"area":"driving"},{"id":"2604.20423","title":"OVPD: A Virtual-Physical Fusion Testing Dataset of OnSite Auton-omous Driving Challenge","created":"2026-04-22","cited_by_count":0,"area":"driving"},{"id":"2606.25127","title":"Reward-Conditioned Attention: How Reward Design Shapes What Autonomous Driving Agents See","created":"2026-06-23","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":"2608.31029","title":"Driving on Memory","created":"2026-08-31","cited_by_count":0,"area":"driving"},{"id":"2609.01799","title":"Designing Versatile Samples for Learned Trajectory Scoring","created":"2026-09-01","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":"2609.38463","title":"TrafficSignBench: Rule-Centric Closed-Loop Evaluation of Traffic-Sign Compliance in Autonomous Driving","created":"2026-09-29","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}