activity
20222026
most citedAdvancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning

1 citations · 3 across the 15 of their papers we have counts for

collaborators
Showing cs.ROShow all

15 papers · 1 filter

cs.RO2026

HEFT: Heavy-Payload Full-size Humanoid Teleoperation with Privileged Motion Guidance and Windowed Payload Curriculum

Chenxin Liu, Qingzhou Lu, Guangxiao Yang +4

General motion tracking and teleoperation offer a promising path to scalable humanoid skill acquisition, yet most existing frameworks are validated on compact platforms or without…

cs.RO2026

Hi-WM: Human-in-the-World-Model for Scalable Robot Post-Training

Yaxuan Li, Zhongyi Zhou, Yefei Chen +5

Post-training is essential for turning pretrained generalist robot policies into reliable task-specific controllers, but existing human-in-the-loop pipelines remain tied to physica…

cs.RO2026

Breaking Lock-In: Preserving Steerability under Low-Data VLA Post-Training

Suning Huang, Jiaqi Shao, Ke Wang +5

Have you ever post-trained a generalist vision-language-action (VLA) policy on a small demonstration dataset, only to find that it stops responding to new instructions and is limit…

cs.RO2026

Veo-Act: How Far Can Frontier Video Models Advance Generalizable Robot Manipulation?

Zhongru Zhang, Chenghan Yang, Qingzhou Lu +4

Video generation models have advanced rapidly and are beginning to show a strong understanding of physical dynamics. In this paper, we investigate how far an advanced video generat…

cs.RO2026

VLAW: Iterative Co-Improvement of Vision-Language-Action Policy and World Model

Yanjiang Guo, Tony Lee, Lucy Xiaoyang Shi +3

The goal of this paper is to improve the performance and reliability of vision-language-action (VLA) models through iterative online interaction. Since collecting policy rollouts i…

cs.RO2026

BagelVLA: Enhancing Long-Horizon Manipulation via Interleaved Vision-Language-Action Generation

Yucheng Hu, Jianke Zhang, Yuanfei Luo +9

Equipping embodied agents with the ability to reason about tasks, foresee physical outcomes, and generate precise actions is essential for general-purpose manipulation. While recen…