Elamur Research⌕
☰
home / authors / Xueyan Zhang

Xueyan Zhang

Xueyan Zhang has 2 papers in our library, in 2025; often with Jinman Zhao, Erxue Min, Gerald Penn.

2 papers in our library · 2025

OpenAlex · ORCID · Wikidata · h-index 10 · 74 works · 396 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 17 times in our library · ⭐ Paper Stars ranking: #8960

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

🎓University of WaterlooWaterloo · Canada2023–2026 · 4 paperscurrent🎓Southwest Jiaotong UniversityChengdu · China2009–2015 · 12 papers🎓Ningbo Open UniversityNingbo · China2008–2022 · 4 papers🎓Beijing Jiaotong UniversityBeijing · China2018–2019 · 4 papers🎓Henan Institute of Science and TechnologyXinxiang · China2023 · 3 papers🎓Guilin University of Electronic TechnologyGuilin · China2018–2019 · 3 papers🎓Liaoning Normal UniversityDalian · China2023–2024 · 2 papers🎓North China University of TechnologyBeijing · China2018–2020 · 2 papers🎓Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing · China2013–2014 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 20 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

 Works by year

2020s

20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. UORA: Uniform Orthogonal Reinitialization Adaptation in Parameter Efficient Fine-Tuning of Large Models (2025 · 14 citations)
    Fully fine-tuning large models is expensive in compute and in storage for per-task checkpoints. LoRA lowers this cost by training low-rank matrices. VeRA goes further: it freezes random projection matrices and trains only two scaling vectors, but it needs a high rank to stay competitive, which raises computation. The…
  2. Tiny Budgets, Big Gains: Parameter Placement Strategy in Parameter Super-Efficient Fine-Tuning (2025 · 8 citations)
    Parameter-efficient fine-tuning methods such as LoRA lower the cost of adapting large models. Yet models now reach hundreds of billions of parameters, so even rank-1 LoRA can be too heavy for mobile hardware or labs with little compute. The authors ask how a very small, fixed budget of trainable parameters should be…

 Co-authors here

8 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 17 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated

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