{"total":25,"rows":[{"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":"2603.29163","title":"SparseDriveV2: Scoring is All You Need for End-to-End Autonomous Driving","created":"2026-03-31","cited_by_count":26,"area":"driving"},{"id":"2506.00034","title":"GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous Driving","created":"2025-05-27","cited_by_count":16,"area":"driving"},{"id":"2507.17596","title":"PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving","created":"2025-07-23","cited_by_count":16,"area":"driving"},{"id":"2603.06049","title":"Devil is in Narrow Policy: Unleashing Exploration in Driving VLA Models","created":"2026-03-06","cited_by_count":15,"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":"2604.00813","title":"DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale","created":"2026-04-01","cited_by_count":13,"area":"driving"},{"id":"2605.15120","title":"CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planning","created":"2026-05-14","cited_by_count":11,"area":"driving"},{"id":"2605.19771","title":"Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives","created":"2026-05-19","cited_by_count":8,"area":"driving"},{"id":"2509.14303","title":"FlowDrive: Energy Flow Field for End-to-End Autonomous Driving","created":"2025-09-17","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":"2603.13842","title":"Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving","created":"2026-03-14","cited_by_count":4,"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":"2605.21139","title":"Distill to Think, Foresee to Act: Cognitive-Physical Reinforcement Learning for Autonomous Driving","created":"2026-05-20","cited_by_count":3,"area":"driving"},{"id":"2508.07838","title":"CBDES MoE: Hierarchically Decoupled Mixture-of-Experts for Functional Modules in Autonomous Driving","created":"2025-08-11","cited_by_count":2,"area":"driving"},{"id":"2605.19524","title":"SafeAlign-VLA: A Negative-Enhanced Safe Alignment Framework for Risk-Aware Autonomous Driving","created":"2026-05-19","cited_by_count":2,"area":"driving"},{"id":"2605.31116","title":"NTR: Neural Token Reconstruction for Scene Token Bottleneck in End-to-End Driving","created":"2026-05-29","cited_by_count":2,"area":"driving"},{"id":"2606.06219","title":"CLEAR: Cognition and Latent Evaluation for Adaptive Routing in End-to-End Autonomous Driving","created":"2026-06-04","cited_by_count":2,"area":"driving"},{"id":"2509.18609","title":"PIE: Perception and Interaction Enhanced End-to-End Motion Planning for Autonomous Driving","created":"2025-09-23","cited_by_count":1,"area":"driving"},{"id":"2602.03112","title":"A Unified Candidate Set with Scene-Adaptive Refinement via Diffusion for End-to-End Autonomous Driving","created":"2026-02-03","cited_by_count":1,"area":"driving"},{"id":"2605.21061","title":"Grounding Driving VLA via Inverse Kinematics","created":"2026-05-20","cited_by_count":1,"area":"driving"},{"id":"2604.28111","title":"GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment","created":"2026-04-30","cited_by_count":0,"area":"driving"},{"id":"2606.04884","title":"D$^3$-MoE:Dual Disentangled Diffusion Mixture-of-Experts for Style-Controllable End-to-End Autonomous Driving","created":"2026-06-03","cited_by_count":0,"area":"driving"},{"id":"2607.10336","title":"PrismAD: Decoupled Planning via Semantic Mixture-of-Planners for End-to-End Autonomous Driving","created":"2026-07-11","cited_by_count":0,"area":"driving"},{"id":"2607.23511","title":"MOJITO: Modal Joint Learning for Unified End-to-End Autonomous Driving","created":"2026-07-26","cited_by_count":0,"area":"driving"}],"next_cursor":null}