Author

Yongqi Xu

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Preprint Sep 2026

TacDyn-WAM: Learning Implicit Tactile Dynamics in a Heterogeneous Visuo-Tactile World Action Model

World action models improve robotic manipulation by conditioning actions on predicted futures, yet existing tactile variants largely inherit video-generation pipelines that reconstruct future tactile observations through iterative denoising. Such prediction can become unreliable under deployment drift: small changes in...

En-Yi Wang, Ming-Xin Wang, Quan Shi et al. · 0 citations

Preprint Aug 2026

StageWAM: Joint-Embedding Stage Prediction for World-Action Models in Robot Manipulation

StageWAM is introduced, which augments a Motus-based World Action Model with Stage-JEPA, a goal-conditioned Joint-Embedding Predictive Architecture (JEPA) predictor, which uses a frozen V-JEPA2 encoder to extract the current-state representation and predicts the latent target of the next inferred stage.

Xiao Liu, Yuguang Yang, Xi Wang et al. · 2 citations · ⚡1