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Peng-Wei Wang

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#artificial intelligence Preprint Sep 2026

DeCAL: Towards Physically-Grounded Dexterous Vision-Language-Action Models via Contact-Aware Latent Co-Imagination

Dexterous manipulation involves contact-rich and fine-grained interactions with the physical world, posing significant challenges for existing vision-language-action (VLA) models due to severe visual occlusions and complex contact dynamics. While recent works have incorporated tactile sensing into robotic manipulation,...

Yan-Kai Fu, Ning Chen, Jun-Kai Zhao et al. · 0 citations
Preprint Aug 2026

4D-WAM: Infusing Spatiotemporal Awareness into World Action Models through Trajectory Fields

4D-WAM is proposed, a model-agnostic training strategy that injects spatiotemporal knowledge from 3D trajectory fields into WAMs through representation alignment, enabling WAMs to learn trajectory-level spatiotemporal representations.

Lishan Yang, Wen-Xuan Song, Xi Wang et al. · 5 citations · ⚡1
Preprint Aug 2026

SLIM-0.5B: Learning Action-Grounded Predictive Latents for Robot Manipulation

SLIM (Self-supervised Latent Interaction Model), a compact 0.5B-parameter latent interaction policy, which matches or exceeds representative large-scale VLA and world-action-model baselines with fewer parameters, no additional embodied pretraining, lower inference latency, and substantially lower GPU memory usage.

Jing-Kai Wang, Zihan Tang, Gu Zhang et al. · 0 citations

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