{"total":30,"rows":[{"id":"2407.18921","title":"Mobile Edge Intelligence for Large Language Models: A Contemporary Survey","created":"2024-07-09","cited_by_count":128,"area":null},{"id":"2411.04954","title":"CAD-MLLM: Unifying Multimodality-Conditioned CAD Generation With MLLM","created":"2024-11-07","cited_by_count":81,"area":null},{"id":"2407.07035","title":"Vision-and-Language Navigation Today and Tomorrow: A Survey in the Era of Foundation Models","created":"2024-07-09","cited_by_count":79,"area":null},{"id":"2401.01454","title":"A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlook","created":"2024-01-02","cited_by_count":66,"area":null},{"id":"2407.00952","title":"SplitLoRA: A Split Parameter-Efficient Fine-Tuning Framework for Large Language Models","created":"2024-07-01","cited_by_count":62,"area":null},{"id":"2404.07569","title":"Can Vehicle Motion Planning Generalize to Realistic Long-tail Scenarios?","created":"2024-04-11","cited_by_count":38,"area":null},{"id":"2411.11252","title":"DrivingSphere: Building a High-fidelity 4D World for Closed-loop Simulation","created":"2024-11-18","cited_by_count":34,"area":null},{"id":"2412.04842","title":"UniMLVG: Unified Framework for Multi-view Long Video Generation with Comprehensive Control Capabilities for Autonomous Driving","created":"2024-12-06","cited_by_count":27,"area":null},{"id":"2503.21411","title":"Exploring the Roles of Large Language Models in Reshaping Transportation Systems: A Survey, Framework, and Roadmap","created":"2025-03-27","cited_by_count":26,"area":null},{"id":"2402.02968","title":"Delving into Multi-modal Multi-task Foundation Models for Road Scene Understanding: From Learning Paradigm Perspectives","created":"2024-02-05","cited_by_count":23,"area":null},{"id":"2412.11694","title":"From Specific-MLLMs to Omni-MLLMs: A Survey on MLLMs Aligned with Multi-modalities","created":"2024-12-16","cited_by_count":22,"area":null},{"id":"2409.04267","title":"An overview of domain-specific foundation model: key technologies, applications and challenges","created":"2024-09-06","cited_by_count":19,"area":null},{"id":"2503.08683","title":"CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving","created":"2025-03-11","cited_by_count":13,"area":null},{"id":"2411.16554","title":"Generating Out-Of-Distribution Scenarios Using Language Models","created":"2024-11-25","cited_by_count":10,"area":null},{"id":"2506.07725","title":"ETA: Efficiency through Thinking Ahead, A Dual Approach to Self-Driving with Large Models","created":"2025-06-09","cited_by_count":9,"area":null},{"id":"2404.06700","title":"Scaling Multi-Camera 3D Object Detection through Weak-to-Strong Eliciting","created":"2024-04-10","cited_by_count":7,"area":null},{"id":"2507.19370","title":"BEV-LLM: Leveraging Multimodal BEV Maps for Scene Captioning in Autonomous Driving","created":"2025-07-25","cited_by_count":6,"area":null},{"id":"2503.05164","title":"A Comprehensive LLM-powered Framework for Driving Intelligence Evaluation","created":"2025-03-07","cited_by_count":5,"area":null},{"id":"2504.04562","title":"Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language Models","created":"2025-04-06","cited_by_count":5,"area":null},{"id":"2506.19769","title":"A Survey of Multi-sensor Fusion Perception for Embodied AI: Background, Methods, Challenges and Prospects","created":"2025-06-24","cited_by_count":5,"area":null},{"id":"2407.16277","title":"When, Where, and What? A Novel Benchmark for Accident Anticipation and Localization with Large Language Models","created":"2024-07-23","cited_by_count":4,"area":null},{"id":"2512.18028","title":"Embodied4C: Measuring What Matters for Embodied Vision-Language Navigation","created":"2025-12-19","cited_by_count":3,"area":null},{"id":"2408.17222","title":"How Could Generative AI Support Compliance with the EU AI Act? A Review for Safe Automated Driving Perception","created":"2024-08-30","cited_by_count":2,"area":null},{"id":"2510.21160","title":"Towards Physics-informed Spatial Intelligence with Human Priors: An Autonomous Driving Pilot Study","created":"2025-10-24","cited_by_count":2,"area":null},{"id":"2604.22260","title":"Towards Safe Mobility: A Unified Transportation Foundation Model enabled by Open-Ended Vision-Language Dataset","created":"2026-04-24","cited_by_count":2,"area":null},{"id":"2509.19657","title":"Large Language Models for Pedestrian Safety: An Application to Predicting Driver Yielding Behavior at Unsignalized Intersections","created":"2025-09-24","cited_by_count":1,"area":null},{"id":"2512.18189","title":"NL2CA: Auto-formalizing Cognitive Decision-Making from Natural Language Using an Unsupervised CriticNL2LTL Framework","created":"2025-12-20","cited_by_count":1,"area":null},{"id":"2409.14170","title":"LFP: Efficient and Accurate End-to-End Lane-Level Planning via Camera-LiDAR Fusion","created":"2024-09-21","cited_by_count":0,"area":null},{"id":"2602.23719","title":"SAGE-LLM: Towards Safe and Generalizable LLM Controller with Fuzzy-CBF Verification and Graph-Structured Knowledge Retrieval for UAV Decision","created":"2026-02-27","cited_by_count":0,"area":null},{"id":"2608.08281","title":"Exploring LLM Capabilities for Situational Understanding and COLREG compliance on real-world maritime navigation scenarios","created":"2026-08-08","cited_by_count":0,"area":null}],"next_cursor":null}