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Zhao Li

Zhao Li has 2 papers in our library, in 2026, most of them on Language models & pretraining.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 4 · 361 works · 219 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1 time in our library · ⭐ Paper Stars ranking: #11767

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

🏛️Chinese Academy of Agricultural SciencesBeijing · China2016–2026 · 41 paperscurrent🎓Beijing Institute of TechnologyBeijing · China2026 · 21 paperscurrent🎓Guizhou UniversityGuiyang · China2026 · 21 paperscurrent🏛️Ministry of Agriculture and Rural AffairsBeijing · China2026 · 16 paperscurrent🎓Anhui Agricultural UniversityHefei · China2018–2026 · 11 paperscurrent🔬Lanzhou Veterinary Research InstituteLanzhou · China2016–2026 · 11 paperscurrent🎓University of Science and Technology BeijingBeijing · China2026 · 11 paperscurrent🎓Shenzhen UniversityShenzhen · China2026 · 10 paperscurrent🎓Zhejiang UniversityHangzhou · China2026 · 10 paperscurrent🎓Lanzhou UniversityLanzhou · China2026 · 9 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 154 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 8The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksMedicine · 1 workArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksHealth Informatics · 1 workInformation Systems · 1 workComputer Vision and Pattern Recognition · 1 work

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

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. SUAT-BMI at MEDIQA-EVAL 2026: An Ensemble Approach to Language Models as Judges for Automatic Rating of Medical Responses (2026 · 1 citation)
    The authors tackle the automatic rating of LLM-generated answers to dermatology and wound-care questions. They predict the scores that clinical experts would assign along several quality dimensions, using data from the English sub-task of the MEDIQA-EVAL 2026 shared task, built on DermaVQA and WoundcareVQA.
  2. SCOPE: Boosting LLM Efficiency with Scoped Position Encoding (2026)
    Explicit positional encodings such as RoPE add compute and memory-access costs, can be fragile under low-precision arithmetic, and often degrade when models run on sequences longer than those seen in training.

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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