Sign-language interpretation in public communication relies on qualified professional interpreters and can be difficult to scale, motivating robotic signing as a complementary accessibility interface. We present RoBoSTAR, a text-conditioned sign language production (SLP) framework for generating human-centric sign moti...
Yu-Jia Zeng, Chensheng Peng, Yu-Xin Chen et al.· 0 citations
A pretrained video world model admits many plausible futures for a scene, but a robot must realize the exact task-conditioned one. To turn world models into executable robot policies, existing methods fine-tune the heavy world model backbone using large-scale robot data and computational resources. Challenging this sta...
Bang Du, Yi-Chen Xie, Shu-Qi Zhao et al.· 0 citations
This work introduces TANGO, the first whole-body vision-language navigation framework for language-conditioned humanoid traversal in cluttered environments, and demonstrates state-of-the-art performance in vision-language navigation, while outperforming strong modular baselines in navigating challenging scenes requirin...
A. Li, Yu-Xin Chen, Zhao-Bo Li et al.· 2 citations
CLIFT: Closed-Loop Iterative Fine-Tuning is introduced, which turns deployment-time reward feedback into API-compatible supervised data and enables closed-loop policy improvement without accessing weights, gradients, likelihoods, or losses-pushing GROD to near-perfect success after two flywheel cycles, all without open...
Yuxin Chen, H. Srikanth, N. Jew et al.· 0 citations
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