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Yu-Xin Chen

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Preprint Sep 2026

RoboSTAR: Next-Scale Autoregressive Sign Language Translation for Humanoid Robots

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
Preprint Sep 2026

One from Infinity: Actualizing Futures from Pretrained World Models into Robot Actions

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
#artificial intelligence Preprint Sep 2026

TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model

We study the problem of navigating cluttered indoor environments with a humanoid robot. Unlike conventional methods that model navigation as a 2D path planning problem, humanoid traversal in cluttered environments requires continuous geometry-aware whole-body adaptation, including coordinated arm placement, torso adjus...

A. Li, Yu-Xin Chen, Zhao-Bo Li et al. · 2 citations
Preprint Jul 2026

CLIFT: Turning Gemini Robotics On-Device into Humanoid Specialists via Non-Invasive Closed-Loop Iterative Fine-Tuning

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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