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Xiaozhuan Liang

Xiaozhuan Liang has 2 papers in our library, in 2021–2023, most of them on Language models & pretraining, Evaluation & benchmarks; often with Ningyu Zhang, Chuanqi Tan, Fei Huang.

2 papers in our library · 2021–2023

OpenAlex · h-index 3 · 7 works · 72 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 107 times in our library · ⭐ Paper Stars ranking: #6936

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

🎓Zhejiang UniversityHangzhou · China2022–2024 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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).Biochemistry, Genetics and Molecular Biology · 2 worksComputer Science · 2 worksMolecular Biology · 2 worksComputational Theory and Mathematics · 1 workComputer Vision and Pattern Recognition · 1 workArtificial Intelligence · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

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

 Works by year

2020s

20231 paper20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models (2023 · 91 citations)
    General-purpose LLMs perform poorly on biomolecular problems. A key reason is the lack of an instruction-format dataset for the field. Such data is costly to annotate, draws on several disciplines, and uses no single standard representation. Mol-Instructions is a public, instruction-style dataset that addresses this…
  2. CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark (2021 · 71 citations)
    Biomedical NLP evaluation resources such as BLURB and PubMedQA are almost entirely English. Chinese, spoken by roughly a quarter of humanity, has had no shared yardstick for medical language understanding. The authors address this with CBLUE, which they describe as the first Chinese benchmark of its kind. It combines…

 Co-authors here

9 co-authors with a page, the most papers together first.

 Cited by

Papers of our library cite their works 107 times (of the 149,439 papers whose bibliographies we read); 19 citing papers with a page here →.

Updated

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