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cs.RO2026
Do Better Visual Representations Always Lead to Better End-to-End Autonomous Driving?
Zihao Zhang, Haochen Tian, Tianyu Li +5
Visual foundation models (VFMs) are increasingly integrated into end-to-end autonomous driving for their powerful representations, yet it remains unclear when these representations…
cs.AI2026
Software-Hardware Co-optimization for Modular E2E AV Paradigm: A Unified Framework of Optimization Approaches, Simulation Environment and Evaluation Metrics
Chengzhi Ji, Xingfeng Li, Zhaodong Lv +4
Modular end-to-end (ME2E) autonomous driving paradigms combine modular interpretability with global optimization capability and have demonstrated strong performance. However, exist…
cs.RO2026
SG-CADVLM: A Context-Aware Decoding Powered Vision Language Model for Safety-Critical Scenario Generation
Hongyi Zhao, Shuo Wang, Qijie He +1
Autonomous Vehicle (AV) requires rigorous testing in safety-critical scenarios for safety validation, yet its validation is hindered by the high cost of field testing and the lack…