1 citations · 1 across the 9 of their papers we have counts for
11 papers
EgoHumanoid-V2: Human-to-Humanoid Transfer of Coordinated Whole-Body Skills for Loco-Manipulation
Jin Chen, Yiming Jiang, Chongyang Xu +8
Human demonstrations capture diverse scenes and rich whole-body skills without requiring robot teleoperation. Prior work on egocentric transfer has emphasized scene generalization…
UR-VC: Unsupervised Robotic Value Correction for Time-Derived Progress Proxies
Lirui Zhao, Modi Shi, Li Chen +3
Modern robot learning systems increasingly rely on dense progress or value signals to evaluate intermediate states, guide policy learning, and detect task completion, making the qu…
NativeMEM: Native Memory Compression for Long-Horizon Robotic Manipulation
Ziye Wang, Modi Shi, Chaojun Ni +5
How can pretrained Vision-Language-Action (VLA) models retain long-horizon visual histories with high-frequency updates without sacrificing efficiency? Existing approaches rely on…
: Resource-Aware Robust Manipulation via Taming Distributional Inconsistencies
Checheng Yu, Chonghao Sima, Gangcheng Jiang +14
High-reliability long-horizon robotic manipulation has traditionally relied on large-scale data and compute to understand complex real-world dynamics. However, we identify that the…
EgoHumanoid: Unlocking In-the-Wild Loco-Manipulation with Robot-Free Egocentric Demonstration
Modi Shi, Shijia Peng, Jin Chen +6
Human demonstrations offer rich environmental diversity and scale naturally, making them an appealing alternative to robot teleoperation. While this paradigm has advanced robot-arm…
WholeBodyVLA: Towards Unified Latent VLA for Whole-Body Loco-Manipulation Control
Haoran Jiang, Jin Chen, Qingwen Bu +8
Humanoid robots require precise locomotion and dexterous manipulation to perform challenging loco-manipulation tasks. Yet existing approaches, modular or end-to-end, are deficient…
EO-1: An Open Unified Embodied Foundation Model for General Robot Control
Delin Qu, Haoming Song, Qizhi Chen +13
The human ability to seamlessly perform multimodal reasoning and physical interaction in the open world is a core goal for general purpose embodied intelligent systems. Recent visi…
Is Diversity All You Need for Scalable Robotic Manipulation?
Modi Shi, Li Chen, Jin Chen +7
Data scaling has driven remarkable success in foundation models for Natural Language Processing (NLP) and Computer Vision (CV), yet the principles of effective data scaling in robo…
Hume: Introducing System-2 Thinking in Visual-Language-Action Model
Haoming Song, Delin Qu, Yuanqi Yao +9
Humans practice slow thinking before performing actual actions when handling complex tasks in the physical world. This thinking paradigm, recently, has achieved remarkable advancem…
Genie Centurion: Accelerating Scalable Real-World Robot Training with Human Rewind-and-Refine Guidance
Wenhao Wang, Jianheng Song, Chiming Liu +13
While Vision-Language-Action (VLA) models show strong generalizability in various tasks, real-world deployment of robotic policy still requires large-scale, high-quality human expe…
AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems
AgiBot World Contributors, AgiBot-World-Contributors, Qingwen Bu +50
We explore how scalable robot data can address real-world challenges for generalized robotic manipulation. Introducing AgiBot World, a large-scale platform comprising over 1 millio…