{"total":77,"rows":[{"id":"2306.16927","title":"End-to-end Autonomous Driving: Challenges and Frontiers","created":"2023-06-29","cited_by_count":490,"area":"driving"},{"id":"2306.07962","title":"Parting with Misconceptions about Learning-based Vehicle Motion Planning","created":"2023-06-13","cited_by_count":242,"area":null},{"id":"2210.17366","title":"Guided Conditional Diffusion for Controllable Traffic Simulation","created":"2022-10-31","cited_by_count":190,"area":"diffusion"},{"id":"2112.05077","title":"Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Prior","created":"2021-12-09","cited_by_count":139,"area":"driving"},{"id":"2109.13333","title":"Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients","created":"2021-09-27","cited_by_count":122,"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":"2402.05746","title":"Editable Scene Simulation for Autonomous Driving via Collaborative LLM-Agents","created":"2024-02-08","cited_by_count":91,"area":"driving"},{"id":"2305.12032","title":"The Waymo Open Sim Agents Challenge","created":"2023-05-19","cited_by_count":86,"area":null},{"id":"2208.12403","title":"BITS: Bi-level Imitation for Traffic Simulation","created":"2022-08-26","cited_by_count":80,"area":null},{"id":"2109.13602","title":"SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policies","created":"2021-09-28","cited_by_count":69,"area":"driving"},{"id":"2205.03195","title":"Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation","created":"2022-05-06","cited_by_count":61,"area":null},{"id":"2303.04116","title":"TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction","created":"2023-03-07","cited_by_count":56,"area":"wm"},{"id":"2405.17372","title":"BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction","created":"2024-05-27","cited_by_count":50,"area":null},{"id":"2412.12129","title":"SceneDiffuser: Efficient and Controllable Driving Simulation Initialization and Rollout","created":"2024-12-05","cited_by_count":48,"area":"diffusion"},{"id":"2311.02738","title":"Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion","created":"2023-11-05","cited_by_count":47,"area":null},{"id":"2212.06437","title":"DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles","created":"2022-12-13","cited_by_count":37,"area":"driving"},{"id":"2107.08142","title":"Autonomy 2.0: Why is self-driving always 5 years away?","created":"2021-07-16","cited_by_count":30,"area":"driving"},{"id":"2109.11094","title":"PredictionNet: Real-Time Joint Probabilistic Traffic Prediction for Planning, Control, and Simulation","created":"2021-09-23","cited_by_count":29,"area":null},{"id":"2211.02131","title":"Safe Real-World Autonomous Driving by Learning to Predict and Plan with a Mixture of Experts","created":"2022-11-03","cited_by_count":29,"area":"driving"},{"id":"2306.15713","title":"Rethinking Closed-loop Training for Autonomous Driving","created":"2023-06-27","cited_by_count":29,"area":"driving"},{"id":"2310.15975","title":"Data-driven Traffic Simulation: A Comprehensive Review","created":"2023-10-24","cited_by_count":29,"area":null},{"id":"2503.22496","title":"Scenario Dreamer: Vectorized Latent Diffusion for Generating Driving Simulation Environments","created":"2025-03-28","cited_by_count":28,"area":"diffusion"},{"id":"2309.14685","title":"DriveSceneGen: Generating Diverse and Realistic Driving Scenarios from Scratch","created":"2023-09-26","cited_by_count":27,"area":null},{"id":"2403.19918","title":"CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning","created":"2024-03-29","cited_by_count":27,"area":"driving"},{"id":"2409.18343","title":"Improving Agent Behaviors with RL Fine-tuning for Autonomous Driving","created":"2024-09-26","cited_by_count":27,"area":"driving"},{"id":"2306.11868","title":"Multiverse Transformer: 1st Place Solution for Waymo Open Sim Agents Challenge 2023","created":"2023-06-20","cited_by_count":25,"area":null},{"id":"2311.01394","title":"Learning Realistic Traffic Agents in Closed-loop","created":"2023-11-02","cited_by_count":24,"area":null},{"id":"2311.15736","title":"SceneDM: Scene-level Multi-agent Trajectory Generation with Consistent Diffusion Models","created":"2023-11-27","cited_by_count":24,"area":"diffusion"},{"id":"2111.06889","title":"DriverGym: Democratising Reinforcement Learning for Autonomous Driving","created":"2021-11-12","cited_by_count":23,"area":"driving"},{"id":"2203.16792","title":"TrajGen: Generating Realistic and Diverse Trajectories with Reactive and Feasible Agent Behaviors for Autonomous Driving","created":"2022-03-31","cited_by_count":23,"area":"driving"},{"id":"2412.17920","title":"Causal Composition Diffusion Model for Closed-loop Traffic Generation","created":"2024-12-23","cited_by_count":22,"area":"diffusion"},{"id":"2410.08453","title":"AdvDiffuser: Generating Adversarial Safety-Critical Driving Scenarios via Guided Diffusion","created":"2024-10-11","cited_by_count":20,"area":"diffusion"},{"id":"2506.21976","title":"SceneDiffuser++: City-Scale Traffic Simulation via a Generative World Model","created":"2025-06-27","cited_by_count":20,"area":"wm"},{"id":"2205.15460","title":"Critic Sequential Monte Carlo","created":"2022-05-30","cited_by_count":16,"area":null},{"id":"2305.18452","title":"Generating Driving Scenes with Diffusion","created":"2023-05-29","cited_by_count":16,"area":null},{"id":"2501.17015","title":"UniMM: A Unified Mixture Model Framework for Multi-Agent Simulation","created":"2025-01-28","cited_by_count":13,"area":null},{"id":"2409.18218","title":"Learning to Drive via Asymmetric Self-Play","created":"2024-09-26","cited_by_count":11,"area":"driving"},{"id":"2303.13830","title":"Editing Driver Character: Socially-Controllable Behavior Generation for Interactive Traffic Simulation","created":"2023-03-24","cited_by_count":10,"area":null},{"id":"2405.03807","title":"UniGen: Unified Modeling of Initial Agent States and Trajectories for Generating Autonomous Driving Scenarios","created":"2024-05-06","cited_by_count":10,"area":null},{"id":"2505.11247","title":"LD-Scene: LLM-Guided Diffusion for Controllable Generation of Adversarial Safety-Critical Driving Scenarios","created":"2025-05-16","cited_by_count":10,"area":"diffusion"},{"id":"2403.17601","title":"LASIL: Learner-Aware Supervised Imitation Learning For Long-term Microscopic Traffic Simulation","created":"2024-03-26","cited_by_count":8,"area":"offlinerl"},{"id":"2406.04300","title":"Text-to-Drive: Diverse Driving Behavior Synthesis via Large Language Models","created":"2024-06-06","cited_by_count":8,"area":"driving"},{"id":"2211.03408","title":"RITA: Boost Driving Simulators with Realistic Interactive Traffic Flow","created":"2022-11-07","cited_by_count":7,"area":null},{"id":"2405.09794","title":"Human-AI Safety: A Descendant of Generative AI and Control Systems Safety","created":"2024-05-16","cited_by_count":7,"area":null},{"id":"2503.05808","title":"DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models","created":"2025-03-04","cited_by_count":7,"area":null},{"id":"2505.21743","title":"Simulating the Unseen: Crash Prediction Must Learn from What Did Not Happen","created":"2025-05-27","cited_by_count":5,"area":null},{"id":"2507.13729","title":"AGENTS-LLM: Augmentative GENeration of Challenging Traffic Scenarios with an Agentic LLM Framework","created":"2025-07-18","cited_by_count":5,"area":"agents"},{"id":"2510.06913","title":"DecompGAIL: Learning Realistic Traffic Behaviors with Decomposed Multi-Agent Generative Adversarial Imitation Learning","created":"2025-10-08","cited_by_count":5,"area":"offlinerl"},{"id":"2208.04559","title":"Analyzing and Enhancing Closed-loop Stability in Reactive Simulation","created":"2022-08-09","cited_by_count":4,"area":null},{"id":"2210.01747","title":"Learning from Demonstrations of Critical Driving Behaviours Using Driver's Risk Field","created":"2022-10-04","cited_by_count":4,"area":"driving"},{"id":"2407.02516","title":"EditFollower: Tunable Car Following Models for Customizable Adaptive Cruise Control Systems","created":"2024-06-23","cited_by_count":4,"area":null},{"id":"2503.05180","title":"Safety-Critical Traffic Simulation with Adversarial Transfer of Driving Intentions","created":"2025-03-07","cited_by_count":4,"area":"driving"},{"id":"2505.00515","title":"Safety-Critical Traffic Simulation with Guided Latent Diffusion Model","created":"2025-05-01","cited_by_count":4,"area":"diffusion"},{"id":"2511.10403","title":"nuPlan-R: A Closed-Loop Planning Benchmark for Autonomous Driving via Reactive Multi-Agent Simulation","created":"2025-11-13","cited_by_count":4,"area":"driving"},{"id":"2306.06401","title":"Long-term Microscopic Traffic Simulation with History-Masked Multi-agent Imitation Learning","created":"2023-06-10","cited_by_count":3,"area":"offlinerl"},{"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":"2412.08685","title":"ChatDyn: Language-Driven Multi-Actor Dynamics Generation in Street Scenes","created":"2024-12-11","cited_by_count":3,"area":null},{"id":"2411.17917","title":"DECODE: Domain-aware Continual Domain Expansion for Motion Prediction","created":"2024-11-26","cited_by_count":2,"area":null},{"id":"2506.23316","title":"SceneStreamer: Continuous Scenario Generation as Next Token Group Prediction","created":"2025-06-29","cited_by_count":2,"area":null},{"id":"2210.02174","title":"CW-ERM: Improving Autonomous Driving Planning with Closed-loop Weighted Empirical Risk Minimization","created":"2022-10-05","cited_by_count":1,"area":"driving"},{"id":"2211.01634","title":"P4P: Conflict-Aware Motion Prediction for Planning in Autonomous Driving","created":"2022-11-03","cited_by_count":1,"area":"driving"},{"id":"2403.04299","title":"LitSim: A Conflict-aware Policy for Long-term Interactive Traffic Simulation","created":"2024-03-07","cited_by_count":1,"area":null},{"id":"2408.15538","title":"TrafficGamer: Reliable and Flexible Traffic Simulation for Safety-Critical Scenarios with Game-Theoretic Oracles","created":"2024-08-28","cited_by_count":1,"area":"driving"},{"id":"2410.15987","title":"Analyzing Closed-loop Training Techniques for Realistic Traffic Agent Models in Autonomous Highway Driving Simulations","created":"2024-10-21","cited_by_count":1,"area":"driving"},{"id":"2503.11771","title":"Controllable Latent Diffusion for Traffic Simulation","created":"2025-03-14","cited_by_count":1,"area":"diffusion"},{"id":"2506.16720","title":"DRARL: Disengagement-Reason-Augmented Reinforcement Learning for Efficient Improvement of Autonomous Driving Policy","created":"2025-06-20","cited_by_count":1,"area":"driving"},{"id":"2511.20726","title":"Learning from Risk: LLM-Guided Generation of Safety-Critical Scenarios with Prior Knowledge","created":"2025-11-25","cited_by_count":1,"area":null},{"id":"2512.05812","title":"Toward Efficient and Robust Behavior Models for Multi-Agent Driving Simulation","created":"2025-12-05","cited_by_count":1,"area":"driving"},{"id":"2605.14201","title":"MAPLE: Latent Multi-Agent Play for End-to-End Autonomous Driving","created":"2026-05-13","cited_by_count":1,"area":"vla"},{"id":"2607.13028","title":"TerraZero: Procedural Driving Simulation for Zero-Demonstration Self-Play at Scale","created":"2026-07-14","cited_by_count":1,"area":"driving"},{"id":"2205.04883","title":"Identical Image Retrieval using Deep Learning","created":"2022-05-10","cited_by_count":0,"area":null},{"id":"2404.18464","title":"MRIC: Model-Based Reinforcement-Imitation Learning with Mixture-of-Codebooks for Autonomous Driving Simulation","created":"2024-04-29","cited_by_count":0,"area":"driving"},{"id":"2410.22752","title":"SoftCTRL: Soft conservative KL-control of Transformer Reinforcement Learning for Autonomous Driving","created":"2024-10-30","cited_by_count":0,"area":"driving"},{"id":"2601.17920","title":"Agentic AI for Self-Driving Laboratories in Soft Matter: Taxonomy, Benchmarks,and Open Challenges","created":"2026-01-25","cited_by_count":0,"area":"driving"},{"id":"2604.12857","title":"Artificial Intelligence for Modeling and Simulation of Mixed Automated and Human Traffic","created":"2026-04-14","cited_by_count":0,"area":null},{"id":"2607.00545","title":"ECoSim: Data Efficient Fine-Tuning for Controllable Traffic Simulation","created":"2026-07-01","cited_by_count":0,"area":null}],"next_cursor":null}