activity
20182026
most citedBenchmarking In-Hand Manipulation

49 citations · 125 across the 28 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

cs.RO2026

What Matters in Quality-Aware VLA Pretraining: A Benchmark and Empirical Study

Mingxuan Yan, Litian Gong, Dihong Huang +19

How should demonstration quality be used during vision-language-action (VLA) pretraining to improve performance after target-task fine-tuning? We compare weighting, filtering, and…

cs.CV2026

RoboTok: A Scalable Data Engine for Internet Demonstration Video Retrieval and Dexterous Manipulation Learning

Howard Qian, Yiting Chen, Yunfei Xie +6

Robot learning increasingly depends on broad and diverse demonstrations, yet collecting robot data remains expensive and difficult to scale across the wide range of real-world task…

cs.RO2026

EgoInfinity: A Web-Scale 4D Hand-Object Interaction Data Engine for Any-View Robot Retargeting and Video-to-Action Robot Learning

Gaotian Wang, Kejia Ren, Andrew Morgan +4

Internet videos constitute the largest reservoir of embodied human manipulation knowledge, yet converting arbitrary RGB footage into actionable robot training data remains a major…

cs.RO2026

Zero-Shot Sim-to-Real Robot Learning: A Dexterous Manipulation Study on Reactive Catching

Kejia Ren, Gaotian Wang, Andrew S. Morgan +1

Dexterous manipulation is physics-intensive and highly sensitive to modeling errors and perception noise, making sim-to-real transfer prohibitively challenging. Domain randomizatio…

cs.RO2026

ManiDreams: An Open-Source Library for Robust Object Manipulation via Uncertainty-aware Task-specific Intuitive Physics

Gaotian Wang, Kejia Ren, Andrew S. Morgan +1

Dynamics models, whether simulators or learned world models, have long been central to robotic manipulation, but most focus on minimizing prediction error rather than confronting a…

cs.CV2026

MotionBits: Video Segmentation through Motion-Level Analysis of Rigid Bodies

Howard H. Qian, Kejia Ren, Yu Xiang +2

Rigid bodies constitute the smallest manipulable elements in the real world, and understanding how they physically interact is fundamental to embodied reasoning and robotic manipul…

cs.RO2026

ManipulationNet: An Infrastructure for Benchmarking Real-World Robot Manipulation with Physical Skill Challenges and Embodied Multimodal Reasoning

Yiting Chen, Kenneth Kimble, Edward H. Adelson +20

Dexterous manipulation enables robots to purposefully alter the physical world, transforming them from passive observers into active agents in unstructured environments. This capab…