---
title: "Who cites Xiaojun Meng — 18 papers of our library"
description: "18 papers of the Elamur Research library cite the works of Xiaojun Meng, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/xiaojun-meng/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/xiaojun-meng/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Xiaojun Meng](https://md.research.elamur.ai/free/en/authors/xiaojun-meng/) / cited by

# Who cites Xiaojun Meng

22 citations of their works from 18 papers of our library (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← Xiaojun Meng](https://md.research.elamur.ai/free/en/authors/xiaojun-meng/)

1. [**Step-3 is Large yet Affordable: Model-system Co-design for Cost-effective Decoding arXiv:2507.19427**StepFun, Bin Wang, Bojun Wang, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/stepfun-2025-step-3-large-yet/)
2. [**Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition arXiv:2505.22375**Hanting Chen, Yasheng Wang, Kai Han, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-pangu-embedded-efficient-dual/)
3. [**Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs arXiv:2505.04519**Yehui Tang, Yichun Yin, Yaoyuan Wang, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/tang-2025-pangu-ultra-moe-train/)
4. **[Dynamic Sampling that Adapts: Self-Aware Iterative Data Persistent Optimization for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/rao-2026-dynamic-sampling-that-adapts-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jun Rao, Xuebo Liu, Hexuan Deng, et al.*2026 · 4 citations*
5. [**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/)
6. **[From Past To Path: Masked History Learning for Next-Item Prediction in Generative Recommendation](https://md.research.elamur.ai/free/en/papers/wei-2026-past-path-masked-history-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kaiwen Wei, Kejun he, Xiaomian Kang, et al.*2026*
7. **[Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling](https://md.research.elamur.ai/free/en/papers/wang-2026-universally-empowering-zeroth-order-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fei Wang, Li Shen, Liang Ding, et al.*2026*

11 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/xiaojun-meng/) — Xiaojun Meng