BrainWAM: Action-Space Coordination of Semantic Priors and Predictive Dynamics for Autonomous Driving
This work proposes BrainWAM, a structured action-space coordination framework that converts semantic reasoning and predictive world modeling into two specialized action-oriented pathways, and aligns them at the level of compact action representations, and introduces an asynchronous rectified-flow inference strategy with decoupled video and action denoising.
Bing Zhan, Shuyao Shang, Shuo Lu et al.
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