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Jingyang Yuan

Jingyang Yuan has 2 papers in our library, in 2025, most of them on Language models & pretraining, GPU & parallel computing, Efficient models & compression; often with Junyu Luo, Zhiping Xiao, Bohan Wu.

2 papers in our library · 2025

OpenAlex · h-index 8 · 33 works · 2,774 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 4,153 times in our library · ⭐ Paper Stars ranking: #6114

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

🎓Peking UniversityBeijing · China2023–2026 · 9 paperscurrent🎓North China Electric Power UniversityBeijing · China2006–2026 · 2 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 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 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Efficient models & compression · 1 workGPU & parallel computing · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention (2025 · 142 citations)
    Standard softmax attention becomes the main cost in long-context language models. The authors estimate it takes 70–80% of decoding latency at 64k tokens. Earlier sparse attention methods often save compute on paper but not in wall-clock time. Many speed up only prefilling or only decoding, clash with GQA/MQA memory…
  2. A Survey on Efficient Large Language Model Training: From Data-centric Perspectives (2025 · 14 citations)
    Post-training is the stage where LLMs acquire instruction following, alignment, reasoning and domain skills.

 Co-authors here

12 of 15 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 4,153 times (of the 149,439 papers whose bibliographies we read); 894 citing papers with a page here →.

Updated

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