13 citations · 20 across the 3 of their papers we have counts for
3 papers
cs.CL2025
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…
cs.CL2024★ 7 cited
Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent
Xingwu Sun, Yanfeng Chen, Yiqing Huang +105
In this paper, we introduce Hunyuan-Large, which is currently the largest open-source Transformer-based mixture of experts model, with a total of 389 billion parameters and 52 bill…
hep-ex2020★ 13 cited
Feasibility and physics potential of detecting B solar neutrinos at JUNO
JUNO collaboration, Angel Abusleme, Thomas Adam +589
The Jiangmen Underground Neutrino Observatory~(JUNO) features a 20~kt multi-purpose underground liquid scintillator sphere as its main detector. Some of JUNO's features make it an…