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20232026
most citedDrEureka: Language Model Guided Sim-To-Real Transfer

7 citations · 21 across the 21 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.RO2024

One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation

Zhendong Wang, Zhaoshuo Li, Ajay Mandlekar +9

Diffusion models, praised for their success in generative tasks, are increasingly being applied to robotics, demonstrating exceptional performance in behavior cloning. However, the…

cs.RO2024★ 1 cited

DexMimicGen: Automated Data Generation for Bimanual Dexterous Manipulation via Imitation Learning

Zhenyu Jiang, Yuqi Xie, Kevin Lin +5

Imitation learning from human demonstrations is an effective means to teach robots manipulation skills. But data acquisition is a major bottleneck in applying this paradigm more br…

cs.RO2024

HOVER: Versatile Neural Whole-Body Controller for Humanoid Robots

Tairan He, Wenli Xiao, Toru Lin +9

Humanoid whole-body control requires adapting to diverse tasks such as navigation, loco-manipulation, and tabletop manipulation, each demanding a different mode of control. For exa…

cs.CV2024★ 1 cited

LongVILA: Scaling Long-Context Visual Language Models for Long Videos

Yukang Chen, Fuzhao Xue, Dacheng Li +15

Long-context capability is critical for multi-modal foundation models, especially for long video understanding. We introduce LongVILA, a full-stack solution for long-context visual…

cs.RO2024★ 7 cited

DrEureka: Language Model Guided Sim-To-Real Transfer

Yecheng Jason Ma, William Liang, Hung-Ju Wang +5

Transferring policies learned in simulation to the real world is a promising strategy for acquiring robot skills at scale. However, sim-to-real approaches typically rely on manual…

cs.CV2024

ARDuP: Active Region Video Diffusion for Universal Policies

Shuaiyi Huang, Mara Levy, Zhenyu Jiang +5

Sequential decision-making can be formulated as a text-conditioned video generation problem, where a video planner, guided by a text-defined goal, generates future frames visualizi…