5 citations · 5 across the 8 of their papers we have counts for
8 papers
RoboTTT: Context Scaling for Robot Policies
Yunfan Jiang, Yevgen Chebotar, Ruijie Zheng +8
Recent robot foundation models operate with single-step or short-history visuomotor context. We introduce Test-Time-Training Robot Policies (RoboTTT), a robot model and training re…
World Action Models are Zero-shot Policies
Seonghyeon Ye, Yunhao Ge, Kaiyuan Zheng +33
State-of-the-art Vision-Language-Action (VLA) models excel at semantic generalization but struggle to generalize to unseen physical motions in novel environments. We introduce Drea…
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…
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…
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…
GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
NVIDIA, :, Johan Bjorck +40
General-purpose robots need a versatile body and an intelligent mind. Recent advancements in humanoid robots have shown great promise as a hardware platform for building generalist…
QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation
Yue Zhao, Fuzhao Xue, Scott Reed +6
We introduce Quantized Language-Image Pretraining (QLIP), a visual tokenization method that combines state-of-the-art reconstruction quality with state-of-the-art zero-shot image u…