Conference

VLP: Vision-Language Preference Learning for Embodied Manipulation.

In Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025

we propose a novel Vision-Language Preference learning framework that learns a vision-language preference model to provide preference feedback for embodied manipulation tasks.

Runze Liu , Chenjia Bai^✉ , Jiafei Lyu , Shengjie Sun , Yali Du , Xiu Li^✉

VLP: Vision-Language Preference Learning for Embodied Manipulation.

Humanoid Whole-Body Locomotion on Narrow Terrain via Dynamic Balance and Reinforcement Learning.

In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025

we propose a novel whole-body locomotion algorithm based on dynamic balance and Reinforcement Learning (RL) that enables humanoid robots to traverse extreme terrains, particularly narrow pathways and unexpected obstacles, using only proprioception.

Weiji Xie , Chenjia Bai^✉ , Jiyuan Shi , Junkai Yang , Yunfei Ge , Weinan Zhang^✉ , Xuelong Li

Humanoid Whole-Body Locomotion on Narrow Terrain via Dynamic Balance and Reinforcement Learning.