2 papers
cs.RO2026
RoboICL: Embodied In-Context Learning with GPT-6 Astra
Fangcheng Liu, Yeqing Shen, Anda Cheng +7
General-purpose vision-language models offer a promising way to zero-shot robot control: \gptastra{} excels at open-ended and language- or image-conditioned manipulation but remain…
cs.RO2026
What Matters in Designing World Action Models: An Empirical Study
Chao Tang, Haoqing Wang, Zilang Cen +9
World Action Models (WAMs) have emerged as a promising paradigm for generalizable robot control. Despite the growing number of WAM systems, existing works often introduce unified s…