--- title: "Weixuan Sun — author profile and papers — Elamur Research" description: "Weixuan Sun, National University of Defense Technology: 3 papers on Elamur Research (2022–2024), h-index 12 — affiliations, topics…" canonical: "https://research.elamur.ai/free/en/authors/weixuan-sun/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/weixuan-sun/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Weixuan Sun # Weixuan Sun Weixuan Sun has 3 papers in our library, in 2022–2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Yiran Zhong](https://md.research.elamur.ai/free/en/authors/yiran-zhong/), [Zhen Qin](https://md.research.elamur.ai/free/en/authors/zhen-qin/), [Dong Li](https://md.research.elamur.ai/free/en/authors/dong-li/). 3 papers in our library · 2022–2024 [OpenAlex](https://openalex.org/A5101643981) · [ORCID](https://orcid.org/0009-0006-0545-1953) · [**h-index 12**](https://openalex.org/authors/A5101643981) · [37 works](https://openalex.org/works?filter=author.id:A5101643981) · [892 citations](https://openalex.org/works?filter=author.id:A5101643981&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/weixuan-sun/#papers) · [🔗 Cited 153 times in our library](https://md.research.elamur.ai/free/en/authors/weixuan-sun/cited-by/) · [⭐ Paper Stars ranking: #6424](https://md.research.elamur.ai/free/en/paper-stars/page/65/#star-6424) 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=Weixuan+Sun) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Weixuan+Sun) · [dblp](https://dblp.org/search?q=Weixuan+Sun) · [ACL Anthology](https://aclanthology.org/search/?q=Weixuan+Sun) ## Affiliations [🎓**National University of Defense Technology** Changsha · China 2024–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/national-university-of-defense-technology/) · [🎓**Australian National University** Canberra · Australia 2022–2024 · 7 papers](https://md.research.elamur.ai/free/en/universities/australian-national-university/) · [🎓**Jilin University** Changchun · China 2018–2024 · 4 papers](https://md.research.elamur.ai/free/en/universities/jilin-university/) · [🎓**Zhejiang University** Hangzhou · China 2019–2021 · 4 papers](https://md.research.elamur.ai/free/en/universities/zhejiang-university/) · [🏢**Sensetime** Beijing · China 2022–2023 · 3 papers](https://md.research.elamur.ai/free/en/companies/sensetime/) · [🔬**Shanghai Artificial Intelligence Laboratory** Shanghai · China 2023–2024 · 2 papers](https://md.research.elamur.ai/free/en/labs/shanghai-artificial-intelligence-laboratory/) · [🏢**Tencent** Shenzhen · China 2024 · 2 papers](https://md.research.elamur.ai/free/en/companies/tencent/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 more institutions on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 6 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 2 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/) 🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/weixuan-sun/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/weixuan-sun/year/2023/) · [**2022** 1 paper](https://md.research.elamur.ai/free/en/authors/weixuan-sun/year/2022/) ## Papers The most cited first (OpenAlex and our library). 1. **[The Devil in Linear Transformer](https://md.research.elamur.ai/free/en/papers/qin-2022-devil-linear-transformer/)** *(2022 · 67 citations)* Kernel-based linear transformers reduce attention cost from quadratic to linear in sequence length, but they usually lose accuracy compared with the standard softmax transformer. 2. **[TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer](https://md.research.elamur.ai/free/en/papers/qin-2023-transnormerllm-faster-better-large/)** *(2023 · 33 citations)* Linear attention promises to remove the quadratic cost of softmax attention. In practice, earlier linear-attention models have trailed Transformers in language-modeling quality and rarely ran faster on real hardware. The authors close this gap with TransNormerLLM, a redesigned version of their TransNormer… 3. **[Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models](https://md.research.elamur.ai/free/en/papers/qin-2024-lightning-attention-2-free/)** *(2024 · 31 citations)* Linear attention should cost O(n) instead of the O(n²) of softmax attention. In causal language modeling, however, existing implementations lose this advantage: the kernel trick needs a cumulative summation (cumsum) that parallelizes poorly on GPUs. Lightning Attention-1 had already reduced the memory-I/O bottleneck… ## Co-authors here 11 co-authors with a page, the most papers together first. - [Yiran Zhong](https://md.research.elamur.ai/free/en/authors/yiran-zhong/) ×3 - [Zhen Qin](https://md.research.elamur.ai/free/en/authors/zhen-qin/) ×3 - [Dong Li](https://md.research.elamur.ai/free/en/authors/dong-li/) ×2 - [Weigao Sun](https://md.research.elamur.ai/free/en/authors/weigao-sun/) ×2 - [Xiaodong Han](https://md.research.elamur.ai/free/en/authors/xiaodong-han/) ×2 - [Xuyang Shen](https://md.research.elamur.ai/free/en/authors/xuyang-shen/) ×2 - [Dongxu Li](https://md.research.elamur.ai/free/en/authors/dongxu-li/) - [Lingpeng Kong](https://md.research.elamur.ai/free/en/authors/lingpeng-kong/) - [Nick M. Barnes](https://md.research.elamur.ai/free/en/authors/nick-m-barnes/) - [Xiao Luo](https://md.research.elamur.ai/free/en/authors/xiao-luo/) - [Yu Qiao](https://md.research.elamur.ai/free/en/authors/yu-qiao/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2022](https://md.research.elamur.ai/free/en/venues/emnlp/2022/) ## Cited by Papers of our library cite their works 153 times (of the 149,439 papers whose bibliographies we read); [27 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/weixuan-sun/cited-by/). Updated 30 October 2026