6 citations · 12 across the 14 of their papers we have counts for
4 papers · 1 filter
How to Better Train VLAs: Lessons Learned From the REAL-I Challenge at ICRA 2026
Jiaming Wang, Jizhuo Chen, Diwen Liu +11
How can robot policies learn more effectively from a fixed demonstration budget? The first Real-world Embodied AI Learning (REAL-I) Challenge at ICRA 2026 examined this question th…
VLA-GSE: Boosting Parameter-Efficient Fine-Tuning in VLA with Generalized and Specialized Experts
Yuhua Jiang, Junjie Lu, Xinyao Qin +4
Vision-language-action (VLA) models inherit rich visual-semantic priors from pre-trained vision-language backbones, but adapting them to robotic control remains challenging. Full f…
CKT-WAM: Parameter-Efficient Context Knowledge Transfer Between World Action Models
Yuhua Jiang, Yijun Guo, Hongbing Yang +7
World action models (WAMs) provide a powerful generative framework for embodied control, yet transferring knowledge across heterogeneous WAMs remains challenging due to mismatched…
AsyncVLA: Asynchronous Flow Matching for Vision-Language-Action Models
Yuhua Jiang, Shuang Cheng, Yan Ding +2
Vision-language-action (VLA) models have recently emerged as a powerful paradigm for building generalist robots. However, traditional VLA models that generate actions through flow…