Recent Vision-Language-Action (VLA) models increasingly use natural-language instructions to condition autonomous driving behavior. Yet existing closed-loop benchmarks primarily measure route completion, safety, and rule compliance, leaving a fundamental question unresolved: does language actually determine which feasi...
Zi-Han You, Ze-Hua Fan, Wenqi Lyu et al.· 0 citations
Autonomous driving requires choosing a safe and efficient plan as surrounding traffic evolves. Generate-and-select planners propose multiple trajectories and score them for execution, and they have outperformed representative direct-prediction baselines on NAVSIM. Their scorer must compare plans that were never execute...
Jie-Yuan Pei, Mei-Yi Lu, Sining Ang et al.· 0 citations
Adaptive-WAM is introduced, a quality-aware multi-exit planner built on a Wan2.2-5B backbone that avoids the iterative classifier-free denoising loop and VAE decoding required for future-video synthesis, while dynamically allocating backbone depth according to trajectory quality.
Sining Ang, Yuguang Yang, Yan Wang· 2 citations
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