Jiaqi Wang

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

Review Sep 2026

WorldReward: Reward Modeling for Camera-Conditioned World Models

This work presents WorldReward, a VLM-based pairwise preference reward model that unifies action-consistency and visual-quality evaluation for camera-conditioned world models, and introduces WorldReward-Bench, a human-annotated benchmark measuring reward-model agreement with human preferences across action consistency,...

Yi-Bin Wang, Ze-Han Wang, Junshu Tang et al. · 0 citations