RoboFlow4D: A Lightweight Flow World Model Toward Real-Time Flow-Guided Robotic Manipulation

Sixu Lin, Huaiyuan Xu, Junliang Chen, Zhuohao Li, Guangming Wang, Yixiong Jing, Sheng Xu, Runyi Zhao, Brian Sheil, Lap-Pui Chau, Guiliang Liu

An end-to-end, goal-oriented 3D flow world model toward real-time flow-guided robotic manipulation.

DyGRO-VLA: Cross-Task Scaling of Vision Language Action Models via Dynamic Grouped Residual Optimization

Sixu Lin, Yunpeng Qing, Litao Liu, Ming Zhou, Ruixing Jin, Xiaoyi Fan, Guiliang Liu

A dynamic grouping residual reinforcement learning framework for Vision-Language Action models.

HWC-Loco: A Hierarchical Whole-Body Control Approach to Robust Humanoid Locomotion

Sixu Lin, Guanren Qiao, Yunxin Tai, Ang Li, Kui Jia, Guiliang Liu

A hierarchical whole-body control approach for robust humanoid locomotion across diverse terrains, robot structures, and disturbance settings.

BiTrajDiff: Bidirectional Trajectory Generation with Diffusion Models for Offline Reinforcement Learning

Yunpeng Qing, Yixiao Chi, Shuo Chen, Shunyu Liu, Kelu Yao, Sixu Lin, Litao Liu, Changqing Zou

A bidirectional diffusion framework for offline reinforcement learning that models both future and history trajectories from intermediate states.

SignBot: Learning Human-to-Humanoid Sign Language Interaction

Guanren Qiao, Sixu Lin, Ronglai Zuo, Zhizheng Wu, Kui Jia, Guiliang Liu

A human-to-humanoid sign language interaction framework spanning motion retargeting, motion control, and generative interaction.

VLAC: A Vision-Language-Action-Critic Model for Robotic Real-World Reinforcement Learning

Shaopeng Zhai, Qi Zhang, Tianyi Zhang, Fuxian Huang, Haoran Zhang, Ming Zhou, Shengzhe Zhang, Litao Liu, Sixu Lin, Jiangmiao Pang

A vision-language-action-critic model that provides dense progress rewards and action generation for real-world robot reinforcement learning.

SMAP: Self-supervised Motion Adaptation for Physically Plausible Humanoid Whole-body Control

Haoyu Zhao^*, Sixu Lin^*, Qingwei Ben, Minyue Dai, Hao Fei, Jingbo Wang, Hua Zou, Junting Dong

A self-supervised motion adaptation framework for physically plausible humanoid whole-body control.

MASQ: Multi-Agent Reinforcement Learning for Single Quadruped Robot Locomotion

Qi Liu, Jingxiang Guo, Sixu Lin, Shuaikang Ma, Jinxuan Zhu, Yanjie Li

A multi-agent reinforcement learning formulation that treats the legs of a single quadruped robot as cooperating agents.