Elamur Research⌕
☰
home / authors / Shen Yan

Shen Yan

Shen Yan has 2 papers in our library, in 2023–2026, most of them on Language models & pretraining, Vision & language; often with Che Liu, Chenyang Yang, Jiachen Liu.

2 papers in our library · 2023–2026

OpenAlex · h-index 3 · 7 works · 99 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 85 times in our library · ⭐ Paper Stars ranking: #7745

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

🎓Northeastern UniversityShenyang · China2023–2024 · 2 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 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 7The 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 worksSocial Sciences · 1 workSociology and Political Science · 1 work

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

 Works by year

2020s

20261 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Efficient Large Language Models: A Survey (2023 · 110 citations)
    Training and running LLMs with billions of parameters is costly. Using LLaMA data, the authors show that training compute rises steeply with model size while inference throughput falls. This survey maps research on cutting these costs and limits itself to techniques for billion-scale models rather than smaller…
  2. Detecting AI-Generated Content on Social Media with Multi-modal Language Models (2026)
    The paper tackles automatic recognition of AI-generated images and videos in social media posts. It addresses three weaknesses of earlier AIGC detectors: they degrade on content from newer generators, they use only one modality, and they rarely justify their decisions. The authors, from Meta, built a data pipeline…

 Co-authors here

12 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 85 times (of the 149,439 papers whose bibliographies we read); 16 citing papers with a page here →.

Updated

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