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cs.AI2026
LLM-MLFFN: Multi-Level Autonomous Driving Behavior Feature Fusion via Large Language Model
Xiangyu Li, Tianyi Wang, Xi Cheng +5
Accurate classification of autonomous vehicle (AV) driving behaviors is critical for safety validation, performance diagnosis, and traffic integration analysis. However, existing a…
cs.AI2026
Found-RL: foundation model-enhanced reinforcement learning for autonomous driving
Yansong Qu, Zihao Sheng, Zilin Huang +6
Reinforcement Learning (RL) has emerged as a dominant paradigm for end-to-end autonomous driving (AD). However, RL suffers from sample inefficiency and a lack of semantic interpret…
cs.AI2025
Traffic expertise meets residual RL: Knowledge-informed model-based residual reinforcement learning for CAV trajectory control
Zihao Sheng, Zilin Huang, Sikai Chen
Model-based reinforcement learning (RL) is anticipated to exhibit higher sample efficiency compared to model-free RL by utilizing a virtual environment model. However, it is challe…