2 papers
cs.RO2026
VLM-SAFE: Vision-Language Model-Guided Safety-Aware Reinforcement Learning with World Models for Autonomous Driving
Yansong Qu, Zilin Huang, Zihao Sheng +4
Autonomous driving policy learning with reinforcement learning (RL) is fundamentally limited by low sample efficiency, weak generalization, and a dependence on unsafe online trial-…
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…