1 citations · 1 across the 1 of their papers we have counts for
4 papers
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
SurgSync: Time-Synchronized Multi-Modal Data Collection Framework and Dataset for Surgical Robotics
Haoying Zhou, Chang Liu, Yimeng Wu +7
Most existing robotic surgery systems adopt a human-in-the-loop paradigm, often with the surgeon directly teleoperating the robotic system. Adding intelligence to these robots woul…
Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs
Yehui Tang, Yichun Yin, Yaoyuan Wang +71
Sparse large language models (LLMs) with Mixture of Experts (MoE) and close to a trillion parameters are dominating the realm of most capable language models. However, the massive…
ParaLBench: A Large-Scale Benchmark for Computational Paralinguistics over Acoustic Foundation Models
Zixing Zhang, Weixiang Xu, Zhongren Dong +5
Computational paralinguistics (ComParal) aims to develop algorithms and models to automatically detect, analyze, and interpret non-verbal information from speech communication, e.…