Results show that making touch available does not by itself ensure effective multimodal fusion, and SoftVTBench provides a common visuo-tactile resource for studying not only whether a policy succeeds, but how it physically interacts with deformable objects and when touch improves that interaction.
Bowen Jing, Ming-Xin Wang, Ruiyang Hao et al.· 2 citations
UMI-Bridge, which uses UMI as an intermediate domain to align representations according to action equivalence rather than pixel similarity, supports action-anchored latent alignment for data-efficient robot learning and UMI-to-robot task transfer.
Hai-Yi Liu, Jin-Ming Ma, Ke Rui et al.· 0 citations
Action-conditioned objectives improve the geometry used by Euclidean-cost, CEM-based latent MPC, and DA-LeWM augments LeWM with inverse-dynamics and demonstration-conditioned goal-action heads, and accelerates convergence and achieves higher online success than LeWM.
Jia-Wei Wang, Ke Rui, Yu-Shen Zuo et al.· 8 citations
GaussianDream demonstrates that training-time current Gaussian reconstruction and future Gaussian prediction provide effective 3D supervision, but its dense VGGT/TGE-based prefix jointly carries state, dynamics, and action-conditioning information.
Yu-Qing Jiang, Zi-Jian Zhang, Wei-Tao Zhou et al.· 1 citation
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
