works on

From the 1 of 14 linked papers with an AI index.

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

The paper introduces RoboTTT, a robot policy that uses test-time training to handle up to 8,000 timesteps of visual‑motor context, enabling one‑shot imitation from video, on‑the‑fl…

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.LG2026

Formalizing Learning from Language Feedback with Provable Guarantees

Wanqiao Xu, Allen Nie, Ruijie Zheng +3

Interactively learning from observation and language feedback is an increasingly studied area driven by the emergence of large language model (LLM) agents. Despite impressive empir…

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…