{"total":23,"rows":[{"id":"2310.03026","title":"LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving","created":"2023-10-04","cited_by_count":190,"area":"driving"},{"id":"2403.04593","title":"Embodied Understanding of Driving Scenarios","created":"2024-03-07","cited_by_count":63,"area":"driving"},{"id":"2402.01105","title":"A Survey for Foundation Models in Autonomous Driving","created":"2024-02-02","cited_by_count":52,"area":"driving"},{"id":"2312.04372","title":"LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs","created":"2023-12-07","cited_by_count":45,"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":"2312.04316","title":"Towards Knowledge-driven Autonomous Driving","created":"2023-12-07","cited_by_count":29,"area":"driving"},{"id":"2502.06419","title":"Occ-LLM: Enhancing Autonomous Driving with Occupancy-Based Large Language Models","created":"2025-02-10","cited_by_count":28,"area":"driving"},{"id":"2503.03074","title":"BEVDriver: Leveraging BEV Maps in LLMs for Robust Closed-Loop Driving","created":"2025-03-05","cited_by_count":26,"area":"driving"},{"id":"2502.14917","title":"Sce2DriveX: A Generalized MLLM Framework for Scene-to-Drive Learning","created":"2025-02-19","cited_by_count":25,"area":"driving"},{"id":"2311.12144","title":"Applications of Large Scale Foundation Models for Autonomous Driving","created":"2023-11-20","cited_by_count":14,"area":"driving"},{"id":"2406.10540","title":"Generating and Evolving Reward Functions for Highway Driving with Large Language Models","created":"2024-06-15","cited_by_count":8,"area":"driving"},{"id":"2403.12176","title":"Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving","created":"2024-03-18","cited_by_count":7,"area":"driving"},{"id":"2505.05240","title":"PADriver: Towards Personalized Autonomous Driving","created":"2025-05-08","cited_by_count":5,"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":"2509.10570","title":"Large Foundation Models for Trajectory Prediction in Autonomous Driving: A Comprehensive Survey","created":"2025-09-11","cited_by_count":3,"area":"driving"},{"id":"2509.23641","title":"From Static to Dynamic: a Survey of Topology-Aware Perception in Autonomous Driving","created":"2025-09-28","cited_by_count":2,"area":"driving"},{"id":"2503.02076","title":"CorrA: Leveraging Large Language Models for Dynamic Obstacle Avoidance of Autonomous Vehicles","created":"2025-03-03","cited_by_count":1,"area":"driving"},{"id":"2601.05806","title":"Modular Autonomy with Conversational Interaction: An LLM-driven Framework for Decision Making in Autonomous Driving","created":"2026-01-09","cited_by_count":1,"area":"driving"},{"id":"2603.02528","title":"LLM-MLFFN: Multi-Level Autonomous Driving Behavior Feature Fusion via Large Language Model","created":"2026-03-03","cited_by_count":0,"area":"driving"},{"id":"2603.11380","title":"DriveXQA: Cross-modal Visual Question Answering for Adverse Driving Scene Understanding","created":"2026-03-11","cited_by_count":0,"area":"driving"},{"id":"2605.04475","title":"Information Coordination as a Bridge: A Neuro-Symbolic Architecture for Reliable Autonomous Driving Scene Understanding","created":"2026-05-06","cited_by_count":0,"area":"driving"},{"id":"2607.04812","title":"TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving","created":"2026-07-06","cited_by_count":0,"area":"driving"},{"id":"2609.00192","title":"LLM-Driven Autonomous Vehicles Inherit Human Driver Biases in Pedestrian Yielding: Results and Implications From A New Benchmark","created":"2026-08-31","cited_by_count":0,"area":"driving"}],"next_cursor":null}