4 citations · 4 across the 4 of their papers we have counts for
4 papers
ForgeVLA: Federated Vision-Language-Action Learning without Language Annotations
Yuhao Zhou, Yunpeng Zhu, Yang Zhou +7
Vision-Language-Action (VLA) models hold great promise for general-purpose robotic intelligence, yet scaling up such models is severely bottlenecked by the high cost of acquiring a…
UISim: An Interactive Image-Based UI Simulator for Dynamic Mobile Environments
Jiannan Xiang, Yun Zhu, Lei Shu +6
Developing and testing user interfaces (UIs) and training AI agents to interact with them are challenging due to the dynamic and diverse nature of real-world mobile environments. E…
Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer
Bowen Tan, Yun Zhu, Lijuan Liu +3
Large language models (LLMs) such as T0, FLAN, and OPT-IML, excel in multi-tasking under a unified instruction-following paradigm, where they also exhibit remarkable generalization…
RedCoast: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs
Bowen Tan, Yun Zhu, Lijuan Liu +5
The recent progress of AI can be largely attributed to large language models (LLMs). However, their escalating memory requirements introduce challenges for machine learning (ML) re…