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20182026
most citedOpen X-Embodiment: Robotic Learning Datasets and RT-X Models

103 citations · 959 across the 132 of their papers we have counts for

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99 papers · 1 filter

cs.RO2026

One Demonstration, Many Objects: Generalizing Manipulation via Local Contact Geometry

Satvik Sharma, Samrat Sahoo, Huang Huang +4

Dexterous manipulation with multi-fingered robot hands promises human-level dexterity, but collecting large-scale dexterous robot hand data remains difficult. Learning from human d…

cs.RO2026

Cross-Embodiment Transfer via Behavior-Aligned Representations

Ajay Sridhar, Jensen Gao, Jonathan Yang +3

Recent progress in large-scale imitation learning for robot manipulation has been driven by leveraging datasets across a wide range of robot embodiments. However, achieving signifi…

cs.RO2026

VIA: Visual Interface Agent for Robot Control

Hengyuan Hu, Priya Sundaresan, Jensen Gao +1

Robot manipulation is a complex task that requires visual understanding, physical reasoning, planning, and closed-loop control. General-purpose foundation models (FMs) have grown r…

cs.RO2026

Proximal State Nudging: Reducing Skill Atrophy from AI Assistance

Megha Srivastava, Jonathan Ouyang, Eric Zhou +6

Skill atrophy, the gradual decline of human capability under AI assistance, poses a safety risk in shared-control of semi-autonomous systems, where operators may be unable to disti…

cs.RO2026

EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models

Perry Dong, Kuo-Han Hung, Tian Gao +2

The ability to efficiently and reliably learn new tasks has been a foundational challenge in robotics. Vision-Language-Action (VLA) models have demonstrated strong generalization a…

cs.RO2026

Will People Enjoy a Robot Trainer? A Case Study with Snoopie the Pacerbot

Maximilian Du, Jennifer Grannen, Shuran Song +1

The physicality of exercise makes the role of athletic trainers unique. Their physical presence allows them to guide a student through a motion, demonstrate an exercise, and give i…