Elamur Research⌕
☰
home / authors / Weixuan Sun

Weixuan Sun

Weixuan Sun has 3 papers in our library, in 2022–2024, most of them on Language models & pretraining; often with Yiran Zhong, Zhen Qin, Dong Li.

3 papers in our library · 2022–2024

OpenAlex · ORCID · h-index 12 · 37 works · 892 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 153 times in our library · ⭐ Paper Stars ranking: #6424

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

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓National University of Defense TechnologyChangsha · China2024–2026 · 2 paperscurrent🎓Australian National UniversityCanberra · Australia2022–2024 · 7 papers🎓Jilin UniversityChangchun · China2018–2024 · 4 papers🎓Zhejiang UniversityHangzhou · China2019–2021 · 4 papers🏢SensetimeBeijing · China2022–2023 · 3 papers🔬Shanghai Artificial Intelligence LaboratoryShanghai · China2023–2024 · 2 papers🏢TencentShenzhen · China2024 · 2 papers

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 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 2 worksHardware and Architecture · 1 work

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 2 works

 Works by year

2020s

20241 paper20231 paper20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. The Devil in 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 (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 (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.

Venues

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

 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 →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/weixuan-sun/