Author

Han-Xuan Li

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Oct 2026

GAS-Robo: Converting Scene Into a Grid-Action Space for LLM-Driven Open-Ended Robotic Manipulation

Generalizing to out-of-distribution scenarios remains a major challenge for traditional robotic manipulation methods trained on closed datasets. Recent approaches leveraging foundation models have significantly improved zero-shot capabilities by utilizing vision-language models, yet many of these methods treat the foun...

Han-Xuan Li, Sen-Wei Xie, Ze-Tao Lin et al. · IEEE Robotics and Automation... · 0 citations

Preprint Aug 2026

UI-Mate: Advancing Open-Weight Foundation GUI Agents with In-Context Demonstrations

Experiments show that UI-Mate-27B sets a new open-weight state of the art on general computer-use benchmarks, substantially improving long-horizon reliability, and makes three contributions to an environment-grounded training stack with in-context demonstration learning.

Zihan Ding, Long-Xu Dou, Qixiao Gao et al. · 1 citation