BehaviorWorldGen：行为感知世界生成闭环动作模型与仿真器
Original title: BehaviorWorldGen: Closing the Loop between Action Models and World Simulators via Controllable Behavior-Aware Structured World Generation
IndustryAI 70
Source: arXiv cs.ROPublish time unverified
arXiv:2608.22187v2 Announce Type: replace Abstract: Modern driving action models are increasingly improved in a self-improvement loop, where a learned world simulator imagines future observations and the resulting data is fed back to refine the action model. However, the bottleneck of this loop lies in the simulators' inability to generate behaviorally plausible responses by surrounding agents, making generated data both unrealistic in interaction and imbalanced in distribution.