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cs.RO2026
EvoAD: Self-Evolving Autonomous Driving via Latent World-Model Guided Post-hoc Reflection
Junjie Yang, Qiming Zhang, Yuyan Li +12
End-to-end autonomous driving systems have achieved rapid progress by learning unified policies that map sensor observations directly to driving trajectories. However, once deploye…
cs.RO2026
From Likelihood to Utility: Quality-Axis Diffusion for End-to-End Autonomous Driving
Junjie Yang, Ziyi Shi, Shuqi Shen +3
Diffusion models have become a dominant paradigm for end-to-end autonomous driving, yet existing planners organize trajectory generation along the Gaussian-noise axis, treating dri…
cs.RO2026
EditWM: Event-Decomposed World Modeling with Incremental Correction for End-to-End Autonomous Driving
Junjie Yang, Qingwei Zeng, Youyou Li +5
World models support autonomous driving by predicting the scene evolution associated with candidate trajectories. Driving dynamics differ in predictability, motivating a distinctio…