---
title: "Xiaojun Meng · Ankang University — author profile and papers"
description: "Xiaojun Meng, Ankang University: 6 papers on Elamur Research (2025–2026), h-index 5 — affiliations, topics, co-authors and who cites them…"
canonical: "https://research.elamur.ai/free/en/authors/xiaojun-meng/"
---
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# Xiaojun Meng

Xiaojun Meng has 6 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Named entity recognition](https://md.research.elamur.ai/free/en/topics/named-entity-recognition/); often with [Jiansheng Wei](https://md.research.elamur.ai/free/en/authors/jiansheng-wei/), [Jun Rao](https://md.research.elamur.ai/free/en/authors/jun-rao/), [Min Zhang](https://md.research.elamur.ai/free/en/authors/min-zhang/).

6 papers in our library · 2025–2026

[OpenAlex](https://openalex.org/A5102202218) · [ORCID](https://orcid.org/0009-0006-4337-9331) · [**h-index 5**](https://openalex.org/authors/A5102202218) · [25 works](https://openalex.org/works?filter=author.id:A5102202218) · [126 citations](https://openalex.org/works?filter=author.id:A5102202218&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/xiaojun-meng/#papers) · [🔗 Cited 22 times in our library](https://md.research.elamur.ai/free/en/authors/xiaojun-meng/cited-by/) · [⭐ Paper Stars ranking: #9169](https://md.research.elamur.ai/free/en/paper-stars/page/92/#star-9169)

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Xiaojun+Meng) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Xiaojun+Meng) · [dblp](https://dblp.org/search?q=Xiaojun+Meng) · [ACL Anthology](https://aclanthology.org/search/?q=Xiaojun+Meng)

## Affiliations

[🎓**Ankang University** Ankang · China 2024–2026 · 2 papers*current*](https://ror.org/053ax8j41) · [🏢**Huawei Technologies** Shenzhen · China 2025–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/companies/huawei-technologies/) · [🔬**Northwest Institute of Nuclear Technology** Xi'an · China 2018–2024 · 10 papers](https://ror.org/04svrh266) · [🎓**Qingdao Agricultural University** Qingdao · China 2024–2025 · 2 papers](https://ror.org/051qwcj72) · [🔬**Beijing Vaccum Electronic Research Institute** Beijing · China 2021–2023 · 2 papers](https://ror.org/04a30tf85)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 8 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Hardware and Architecture · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/hardware-and-architecture/) · [Experimental and Cognitive Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/)

🧭 Topics 4 Research subjects and languages the work is about.[Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Named entity recognition · 1 work](https://md.research.elamur.ai/free/en/topics/named-entity-recognition/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/)

## Works by year

### 2020s

[**2026** 4 papers](https://md.research.elamur.ai/free/en/authors/xiaojun-meng/year/2026/) · [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/xiaojun-meng/year/2025/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Pangu Ultra: Pushing the Limits of Dense Large Language Models on Ascend NPUs](https://md.research.elamur.ai/free/en/papers/yin-2025-pangu-ultra-pushing-limits/)** *(2025 · 6 citations)* Pangu Ultra is Huawei's effort to show that a very deep dense Transformer, trained entirely on Ascend NPUs instead of GPUs, can compete with much larger sparse MoE systems.
2. **[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/)** *(2026 · 4 citations)* Data selection for training math-reasoning LLMs usually depends on fixed difficulty labels or external scorers.
3. **[Pangu Pro MoE: Mixture of Grouped Experts for Efficient Sparsity](https://md.research.elamur.ai/free/en/papers/tang-2025-pangu-pro-moe-mixture/)** *(2025 · 4 citations)* Sparse Mixture-of-Experts LLMs are cheap per token. However, when experts are spread across accelerators, uneven routing overloads some devices, and the slowest device limits overall speed. The Pangu Team at Huawei proposes Mixture of Grouped Experts (MoGE). Experts are split into equal, non-overlapping groups…
4. **[MathAgent: Adversarial Evolution of Constraint Graphs for Mathematical Reasoning Data Synthesis](https://md.research.elamur.ai/free/en/papers/yu-2026-mathagent-adversarial-evolution-constraint-graphs/)** *(2026 · 3 citations)* Synthetic data for mathematical reasoning is often built either by mutating human-curated seed problems, which limits diversity to the seeds' scope, or by prompting models from scratch, which tends toward repetitive, shallow problems (mode collapse).
5. **[Why Did Apple Fall: Evaluating Curiosity in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-why-did-apple-fall-evaluating/)** *(2026 · 1 citation)* Curiosity-inspired intrinsic rewards are increasingly used in RL training of LLMs, but it has not been checked whether these models actually behave in curious ways, or whether the reported gains simply come from amplified statistical signals such as entropy.
6. **[Memory-Guided Hard Data Augmentation for Multimodal Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/liu-2026-memory-guided-hard-data-augmentation/)** *(2026)* The paper targets data augmentation for Multimodal Named Entity Recognition (MNER), where images help disambiguate text.

## Co-authors here

12 of 27 co-authors with a page, the most papers together first.

- [Jiansheng Wei](https://md.research.elamur.ai/free/en/authors/jiansheng-wei/) ×4
- [Jun Rao](https://md.research.elamur.ai/free/en/authors/jun-rao/) ×2
- [Min Zhang](https://md.research.elamur.ai/free/en/authors/min-zhang/) ×2
- [Wei Guo](https://md.research.elamur.ai/free/en/authors/wei-guo/) ×2
- [Yanghua Xiao](https://md.research.elamur.ai/free/en/authors/yanghua-xiao/) ×2
- [Yaoyuan Wang](https://md.research.elamur.ai/free/en/authors/yaoyuan-wang/) ×2
- [Yehui Tang](https://md.research.elamur.ai/free/en/authors/yehui-tang/) ×2
- [Zixiong Yu](https://md.research.elamur.ai/free/en/authors/zixiong-yu/) ×2
- [Bo Xu](https://md.research.elamur.ai/free/en/authors/bo-xu/)
- [Bohan Li](https://md.research.elamur.ai/free/en/authors/bohan-li/)
- [Can Chen](https://md.research.elamur.ai/free/en/authors/can-chen/)
- [Dong Li](https://md.research.elamur.ai/free/en/authors/dong-li/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×4: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×4

## Cited by

Papers of our library cite their works 22 times (of the 149,439 papers whose bibliographies we read); [7 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/xiaojun-meng/cited-by/).

Updated 1 November 2026
