activity
20172026
most citedExperience-driven Networking: A Deep Reinforcement Learning based Approach

50 citations · 122 across the 37 of their papers we have counts for

collaborators

44 papers

cs.RO2026

HAF: Adapting Generalist VLAs to Humanoid Whole-Body Loco-manipulation via Hierarchical Action Flow and Spectral Latent RL

Langzhe Gu, Chengkai Hou, Meng Li +14

Humanoid robots hold great promise as general-purpose agents in human-centered environments, yet generalist vision-language-action (VLA) foundation models are not readily applicabl…

cs.CV2026

PlayWorld: Benchmarking World Models with Agent Players over Long-Horizon Objectives

Kaixin Ding, Xi Chen, Minghong Cai +9

Video world models simulate future states conditioned on current observations and user actions. Recent systems have demonstrated impressive video consistency and action controllabi…

cs.RO2026

HEX: Humanoid-Aligned Experts for Cross-Embodiment Whole-Body Manipulation

Shuanghao Bai, Meng Li, Xinyuan Lv +14

Humans achieve complex manipulation through coordinated whole-body control, whereas most Vision-Language-Action (VLA) models treat robot body parts largely independently, making hi…

cs.RO2026

Heracles: Bridging Precise Tracking and Generative Synthesis for General Humanoid Control

Zelin Tao, Zeran Su, Peiran Liu +13

Achieving general-purpose humanoid control requires a delicate balance between the precise execution of commanded motions and the flexible, anthropomorphic adaptability needed to r…

cs.RO2026

Load-Aware Locomotion Control for Humanoid Robots in Industrial Transportation Tasks

Lequn Fu, Yijun Zhong, Xiao Li +4

Humanoid robots deployed in industrial environments are required to perform load-carrying transportation tasks that tightly couple locomotion and manipulation. However, achieving s…

cs.RO2025

Real-world Reinforcement Learning from Suboptimal Interventions

Yinuo Zhao, Huiqian Jin, Lechun Jiang +9

Real-world reinforcement learning (RL) offers a promising approach to training precise and dexterous robotic manipulation policies in an online manner, enabling robots to learn fro…