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Fei Yang

Fei Yang has 2 papers in our library, in 2026, most of them on Language models & pretraining, Efficient models & compression; often with Changhai Zhou, Jun Gao, Pan Zhang.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 8 · 16 works · 341 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1 time in our library · ⭐ Paper Stars ranking: #10903

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

🎓Nanjing University of Science and TechnologyNanjing · China2018–2025 · 6 paperscurrent🎓Central South UniversityChangsha · China2020–2023 · 3 papers🎓Shandong UniversityJinan · China2021–2024 · 2 papers

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 5The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 work

🧭 Topics 2Research subjects and languages the work is about.Efficient models & compression · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Linguistic Steganography via Self-Adjusting Asymmetric Number System (2026 · 2 citations)
    Generative linguistic steganography hides a secret bitstream inside text produced by a language model. Existing coding schemes (fixed-length, Huffman, arithmetic coding, ADG) give little control over payload size and tend to sacrifice naturalness for capacity. The authors introduce SA-ANS, which they describe as the…
  2. Deputy: Accelerating Large Language Model Inference with Dynamic Low-Rank Substitution (2026 · 1 citation)
    Large language models apply the same dense computation to every token, which wastes resources and slows inference.

 Co-authors here

7 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 1 time (of the 149,439 papers whose bibliographies we read).

Updated

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