Reproduce “RhinoVLA Technical Report” on OpenResearch

Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.

Universal app for Apple silicon and Intel. Requires macOS 11 or later.

About this paper

Huixi Technology, Chen Zhang, Chenyang Zhou, Guanglei Ding, Guanghui He, Haibin Gao, Jiajia Chen, Jianyong Zhang and 7 more

RhinoVLA pairs a reduced-token visual-language backbone with a continuous-action expert, a shared 72D cross-robot interface, and hardware-specific inference optimizations. The authors report 11.69 Hz on Huixi R1, exceeding the 10 Hz target, not a hardware-matched comparison with π0.5. Table 4 reports a 96.6% LIBERO average with View Registry versus π0.5’s 96.9%, though accompanying prose gives 94.1%.

Summary by alphaXiv.

Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.