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Zunhai Su

Zunhai Su has 2 papers in our library, in 2026, most of them on Language models & pretraining, Interpretability, Efficient models & compression; often with Chenming Shang, Ercong Nie, Hengyuan Zhang.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 1 · 29 works · 2 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 14 times in our library · ⭐ Paper Stars ranking: #9581

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

🎓Tsinghua UniversityBeijing · China2026 · 12 paperscurrent🎓University of Hong KongPok Fu Lam · China2026 · 6 paperscurrent🎓Tsinghua Shenzhen International Graduate SchoolShenzhen · China2026 · 3 paperscurrent🏢MeituanBeijing · China2026 · 1 papercurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 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 worksLanguage and Linguistics · 2 worksEngineering · 1 workComputer Vision and Pattern Recognition · 1 workElectrical and Electronic Engineering · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 2 worksInterpretability · 1 workEfficient models & compression · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models (2026 · 9 citations)
    Most earlier reviews of mechanistic interpretability (MI) in LLMs describe what researchers have discovered inside models.
  2. Exploring Layer-wise Information Effectiveness for Post-Training Quantization in Small Language Models (2026 · 5 citations)
    Compressing small language models (under 8B parameters) to about 2 bits per weight usually ruins their accuracy.

 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 14 times (of the 149,439 papers whose bibliographies we read); 5 citing papers with a page here →.

Updated

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