---
title: "Who cites Pangu Ultra MoE: How to Train — 8 citing papers"
description: "8 papers of the Elamur Research library cite «Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/tang-2025-pangu-ultra-moe-train/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/tang-2025-pangu-ultra-moe-train/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Pangu Ultra MoE: How to Train Your Big MoE on…](https://md.research.elamur.ai/free/en/papers/tang-2025-pangu-ultra-moe-train/) / cited by

# Who cites «Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs»

8 papers of our library cite it (of the 149,439 whose bibliographies we read) · 1 with a page here, the most cited first · [← back to «Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs»](https://md.research.elamur.ai/free/en/papers/tang-2025-pangu-ultra-moe-train/)

1. [**Pangu Pro MoE: Mixture of Grouped Experts for Efficient Sparsity arXiv:2505.21411**Yehui Tang, Xiaosong Li, Fangcheng Liu, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/tang-2025-pangu-pro-moe-mixture/)

7 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/tang-2025-pangu-ultra-moe-train/) — Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs