Under-Review

Learn as Individuals, Evolve as a Team: Multi-agent LLMs Adaptation in Embodied Environments
under review at ARR rounding 2026
We propose the Learn as Individuals, Evolve as a Team (LIET) framework to enable multi-agent LLMs to adapt to embodied environments through individual learning and team evolution
Xinran Li , Chenjia Bai✉ , Zijian Li , Jiakun Zheng , Ting Xiao , Jun Zhang✉
PDF Cite
Learn as Individuals, Evolve as a Team: Multi-agent LLMs Adaptation in Embodied Environments
KungfuBot2: Learning Versatile Motion Skills for Humanoid Whole-Body Control
under review
We present VMS, a unified whole-body controller that enables humanoid robots to learn diverse and dynamic behaviors within a single policy through hybrid tracking and orthogonal mixture of experts.
Jinrui Han , Weiji Xie , Jiakun Zheng , Jiyuan Shi , Weinan Zhang , Ting Xiao , Chenjia Bai✉
PDF Cite Code Project
KungfuBot2: Learning Versatile Motion Skills for Humanoid Whole-Body Control
Align-Then-stEer: Adapting the Vision-Language Action Models through Unified Latent Guidance
under review
We propose Align-Then-stEer (ATE), a framework that adapts VLAs to novel robots and tasks through unified latent guidance. ATE can handle significant domain shifts without compromising performance and compatible to Pi0, RDT, and etc.
Yang Zhang , Chenwei Wang , Ouyang Lu , Yuan Zhao , Yunfei Ge , Zhenglong Sun , Xiu Li , Chi Zhang , Chenjia Bai✉ , Xuelong Li✉
PDF Cite Code Project 公众号
Align-Then-stEer: Adapting the Vision-Language Action Models through Unified Latent Guidance