World action models jointly predict future visual observations and actions, whereas existing tactile-aware variants typically represent future touch as an image or latent stream without modeling the physical dependencies that organize tactile states hierarchically. We present HiTac-WAM, a hierarchical tactile world act...
Chao Xue, Chao-Fan Zhang, Wenxuan Ma et al.· 3 citations
Long-horizon robot manipulation reuses skills across many task compositions, but improving these compositions with additional end-to-end demonstrations is costly. A practical self-improving system must decide both what to teach next and where to apply that supervision. We present ROBOCOACH, a world-model-guided coachin...
Jia-Jun Liu, Yi-Fan Chen, Yi-Chao Liu et al.· 0 citations
Completeness-aware Motion Correspondence (CMC), a ground-truth-anchored evaluation protocol that jointly measures localization, trajectory completeness, visibility, and continuity, counting missing predictions as failures on visible dynamic points, is introduced.
Kun-Wei Wu, Xiang Liu, Guo-Cai Yao et al.· 0 citations
DeCAL is presented, a physically-grounded dexterous vision-language-action model that unifies understanding, imagination and action generation for contact-rich dexterous manipulation and introduces Adaptive Visuo-Tactile Fusion that dynamically regulates tactile interactions via a contact-aware gating strategy.
Yan-Kai Fu, Ning Chen, Jun-Kai Zhao et al.· 0 citations
VERDI is proposed, a continual framework for evidence-licensed world model optimization that characterizes each world model through shared inference-time probes to construct an Optimization Fin- gerprint, retrieves relevant prior experience as ranked hypotheses, and validates every candidate under a frozen target-side...
Jun-Yu Wu, Shiqin Nie, Youyi Kou et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
