7 citations · 21 across the 21 of their papers we have counts for
21 papers
GLM-5: from Vibe Coding to Agentic Engineering
GLM-5-Team, :, Aohan Zeng +184
We present GLM-5, a next-generation foundation model designed to transition the paradigm of vibe coding to agentic engineering. Building upon the agentic, reasoning, and coding (AR…
EgoScale: Scaling Dexterous Manipulation with Diverse Egocentric Human Data
Ruijie Zheng, Dantong Niu, Yuqi Xie +12
Human behavior is among the most scalable sources of data for learning physical intelligence, yet how to effectively leverage it for dexterous manipulation remains unclear. While p…
CHIP: Adaptive Compliance for Humanoid Control through Hindsight Perturbation
Sirui Chen, Zi-ang Cao, Zhengyi Luo +7
Recent progress in humanoid robots has unlocked agile locomotion skills, including backflipping, running, and crawling. Yet it remains challenging for a humanoid robot to perform f…
VIRAL: Visual Sim-to-Real at Scale for Humanoid Loco-Manipulation
Tairan He, Zi Wang, Haoru Xue +11
A key barrier to the real-world deployment of humanoid robots is the lack of autonomous loco-manipulation skills. We introduce VIRAL, a visual sim-to-real framework that learns hum…
World Simulation with Video Foundation Models for Physical AI
NVIDIA, :, Arslan Ali +87
We introduce [Cosmos-Predict2.5], the latest generation of the Cosmos World Foundation Models for Physical AI. Built on a flow-based architecture, [Cosmos-Predict2.5] unifies Text2…
GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models
5 Team, Aohan Zeng, Xin Lv +167
We present GLM-4.5, an open-source Mixture-of-Experts (MoE) large language model with 355B total parameters and 32B activated parameters, featuring a hybrid reasoning method that s…
DreamGen: Unlocking Generalization in Robot Learning through Video World Models
Joel Jang, Seonghyeon Ye, Zongyu Lin +25
We introduce DreamGen, a simple yet highly effective 4-stage pipeline for training robot policies that generalize across behaviors and environments through neural trajectories - sy…
FLARE: Robot Learning with Implicit World Modeling
Ruijie Zheng, Jing Wang, Scott Reed +18
We introduce uture tent presentation Alignment (), a novel framework that integrates predictive latent world modeling into rob…
Emergent Active Perception and Dexterity of Simulated Humanoids from Visual Reinforcement Learning
Zhengyi Luo, Chen Tessler, Toru Lin +8
Human behavior is fundamentally shaped by visual perception -- our ability to interact with the world depends on actively gathering relevant information and adapting our movements…
SCIZOR: A Self-Supervised Approach to Data Curation for Large-Scale Imitation Learning
Yu Zhang, Yuqi Xie, Huihan Liu +4
Imitation learning advances robot capabilities by enabling the acquisition of diverse behaviors from human demonstrations. However, large-scale datasets used for policy training of…
DexUMI: Using Human Hand as the Universal Manipulation Interface for Dexterous Manipulation
Mengda Xu, Han Zhang, Yifan Hou +4
We present DexUMI - a data collection and policy learning framework that uses the human hand as the natural interface to transfer dexterous manipulation skills to various robot han…
Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation
Abhiram Maddukuri, Zhenyu Jiang, Lawrence Yunliang Chen +12
Large real-world robot datasets hold great potential to train generalist robot models, but scaling real-world human data collection is time-consuming and resource-intensive. Simula…
Sim-to-Real Reinforcement Learning for Vision-Based Dexterous Manipulation on Humanoids
Toru Lin, Kartik Sachdev, Linxi Fan +2
Learning generalizable robot manipulation policies, especially for complex multi-fingered humanoids, remains a significant challenge. Existing approaches primarily rely on extensiv…
One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation
Zhendong Wang, Zhaoshuo Li, Ajay Mandlekar +9
Diffusion models, praised for their success in generative tasks, are increasingly being applied to robotics, demonstrating exceptional performance in behavior cloning. However, the…
DexMimicGen: Automated Data Generation for Bimanual Dexterous Manipulation via Imitation Learning
Zhenyu Jiang, Yuqi Xie, Kevin Lin +5
Imitation learning from human demonstrations is an effective means to teach robots manipulation skills. But data acquisition is a major bottleneck in applying this paradigm more br…
HOVER: Versatile Neural Whole-Body Controller for Humanoid Robots
Tairan He, Wenli Xiao, Toru Lin +9
Humanoid whole-body control requires adapting to diverse tasks such as navigation, loco-manipulation, and tabletop manipulation, each demanding a different mode of control. For exa…
LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Yukang Chen, Fuzhao Xue, Dacheng Li +15
Long-context capability is critical for multi-modal foundation models, especially for long video understanding. We introduce LongVILA, a full-stack solution for long-context visual…
DrEureka: Language Model Guided Sim-To-Real Transfer
Yecheng Jason Ma, William Liang, Hung-Ju Wang +5
Transferring policies learned in simulation to the real world is a promising strategy for acquiring robot skills at scale. However, sim-to-real approaches typically rely on manual…
ARDuP: Active Region Video Diffusion for Universal Policies
Shuaiyi Huang, Mara Levy, Zhenyu Jiang +5
Sequential decision-making can be formulated as a text-conditioned video generation problem, where a video planner, guided by a text-defined goal, generates future frames visualizi…
MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations
Ajay Mandlekar, Soroush Nasiriany, Bowen Wen +5
Imitation learning from a large set of human demonstrations has proved to be an effective paradigm for building capable robot agents. However, the demonstrations can be extremely c…
Cross-Episodic Curriculum for Transformer Agents
Lucy Xiaoyang Shi, Yunfan Jiang, Jake Grigsby +2
We present a new algorithm, Cross-Episodic Curriculum (CEC), to boost the learning efficiency and generalization of Transformer agents. Central to CEC is the placement of cross-epi…