{"total":17,"rows":[{"id":"2501.15564","title":"Diffusion-Based Planning for Autonomous Driving with Flexible Guidance","created":"2025-01-26","cited_by_count":141,"area":"driving"},{"id":"2504.19580","title":"ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving","created":"2025-04-28","cited_by_count":67,"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":"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":"2604.11734","title":"SCORP: Scene-Consistent Multi-agent Diffusion Planning with Stable Online Reinforcement Post-Training for Cooperative Driving","created":"2026-04-13","cited_by_count":2,"area":"driving"},{"id":"2606.11019","title":"Diffusion Forcing Planner: History-Annealed Planning with Time-Dependent Guidance for Autonomous Driving","created":"2026-06-09","cited_by_count":2,"area":"driving"},{"id":"2407.06317","title":"Enhanced Safety in Autonomous Driving: Integrating Latent State Diffusion Model for End-to-End Navigation","created":"2024-07-08","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":"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":"2506.12283","title":"Deep Fictitious Play-Based Potential Differential Games for Learning Human-Like Interaction at Unsignalized Intersections","created":"2025-06-14","cited_by_count":0,"area":"driving"},{"id":"2512.18662","title":"Pseudo-Expert Regularized Offline RL for End-to-End Autonomous Driving in Photorealistic Closed-Loop Environments","created":"2025-12-21","cited_by_count":0,"area":"driving"},{"id":"2605.13751","title":"Learning Responsibility-Attributed Adversarial Scenarios for Testing Autonomous Vehicles","created":"2026-05-13","cited_by_count":0,"area":"driving"},{"id":"2606.30807","title":"Off the Rails: Hijacking the Scoring Head in Generative End-to-End Driving Planners with Safety-Violating Adversarial Perturbations","created":"2026-06-29","cited_by_count":0,"area":"driving"},{"id":"2609.31383","title":"Guiding End-to-End Driving Models with Endpoint-Constrained Trajectory Optimization","created":"2026-09-25","cited_by_count":0,"area":"driving"},{"id":"2609.38472","title":"Diffusion-2BC: Hybrid Diffusion and Regression Training for Offline Behavior Cloning 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"},{"id":"2610.04366","title":"Human Behavior-Informed Crash Scenario Generation with Real-World Crash Priors for Autonomous Vehicle Safety Evaluation","created":"2026-10-03","cited_by_count":0,"area":"driving"}],"next_cursor":null}