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Preprint Aug 2026

BehaviorWorldGen: Closing the Loop between Action Models and World Simulators via Controllable Behavior-Aware Structured World Generation

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 response...

Jia-Qi Wang, Zhuo Zhang, Hai-Ning Guan et al. · 0 citations
Preprint Aug 2026

BehaviorWorldGen: Closing the Loop between Action Models and World Simulators via Controllable Behavior-Aware Structured World Generation

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 response...

Jiaqi Wang, Zhuo Zhang, Hai-Ning Guan et al. · 0 citations
Preprint Jul 2026

ROAD: Reciprocal-Objective Alignment of Discriminative Semantics for 3D Shape Generation

High-fidelity 3D generation predominantly relies on scaling model capacity and data, which incurs prohibitive computational costs. This paradigm typically requires learning geometry from scratch and overlooks the rich semantic and structural priors already encapsulated in discriminative 3D foundation models. We contend...

Xiao Luo, Mingyang Du, Xin Zhou et al. · 0 citations

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