Author

Bailin Li

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Preprint Oct 2026

SimVTA: Simulation-Grounded Video-Trajectory Alignment for Driving World Action Models

Driving world action models (WAMs) learn from paired trajectories and future observations. Post-training with reinforcement learning allows the policy to explore alternative trajectories and improve planning using driving rewards. However, driving logs contain future videos only for the recorded trajectories, leaving t...

Chang-Hui Jing, Hao-Chen Tian, Hong-Chen Li et al. · 0 citations

Preprint Aug 2026

MobileWAM: Bridging World Action Models to Mobile Manipulation with Chain-of-Foresight

MobileWAM surpasses state-of-the-art mobile manipulation policies on ManiSkill-HAB and fine-tunes to a real ARX Lift2 mobile manipulator across diverse tasks with strong generalization.

Ze-Hua Fan, Jun-Jie He, Wen-Xuan Song et al. · 3 citations · ⚡1

Jul 2026

FoMoVLA: Bridging Visual Foresight and Motion Guidance for Vision-Language-Action Models

FoMoVLA is proposed, a framework that augments VLA representations with explicit spatio-temporal supervision by jointly learning future feature foresight and sparse 2D point tracking, enhancing the continuous action policy.

Wei Li, Peijin Jia, Yuan Ma et al. · arXiv.org · 0 citations