most citedGR00T N1: An Open Foundation Model for Generalist Humanoid Robots

5 citations · 6 across the 14 of their papers we have counts for

collaborators

14 papers

cs.RO2026

Beyond Episodic Evaluation: Memory Architectural Bottlenecks in Sequential Embodied Question Answering

Zikui Cai, Kaushal Janga, Tan Dat Dao +15

Embodied question answering (EQA) is traditionally evaluated under an episodic formulation, where agents solve each task independently and reset internal state between episodes. Ho…

cs.RO2026

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…

cs.RO2026

T-Rex: Tactile-Reactive Dexterous Manipulation

Dantong Niu, Zhuoyang Liu, Zekai Wang +31

The ability to react dynamically to tactile signals has long been considered crucial to agile human-level dexterity. Yet contemporary learning-based Vision-Language-Action (VLA) mo…

cs.RO2026

Contrastive Action-Image Pre-training for Visuomotor Control

Yuvan Sharma, Dantong Niu, Anirudh Pai +16

Existing vision encoders for robotics face a fundamental bottleneck: robotic datasets lack the scale necessary for large-scale pre-training. Prior work circumvents this data scarci…

cs.RO2026

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…

cs.RO2026

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…