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Zhang-Ren Chen

Zhang-Ren Chen has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining; often with Biqing Qi, Bowen Zhou, Haoxiang Li.

2 papers in our library · 2023–2024

OpenAlex · h-index 5 · 12 works · 76 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 122 times in our library · ⭐ Paper Stars ranking: #9297

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

🏥First Affiliated Hospital of Jiangxi Medical CollegeNanchang · China2026 · 1 papercurrent🎓Nanchang UniversityNanchang · China2026 · 1 papercurrent🏥First Affiliated Hospital of Nanchang UniversityNanchang · China2020–2024 · 7 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 9The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksBiochemistry, Genetics and Molecular Biology · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksMolecular Biology · 2 worksComputer Vision and Pattern Recognition · 1 workHealth Informatics · 1 workMedicine · 1 work

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

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Large Language Models are Zero Shot Hypothesis Proposers (2023 · 45 citations)
    The paper examines whether large language models can formulate new scientific hypotheses without being trained on them, a step in research that has received far less study than hypothesis validation.
  2. Large Language Models as Biomedical Hypothesis Generators: A Comprehensive Evaluation (2024 · 19 citations)
    The paper asks whether large language models can propose genuinely new biomedical hypotheses, rather than repeating knowledge absorbed during pre-training.

 Co-authors here

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

 Cited by

Papers of our library cite their works 122 times (of the 149,439 papers whose bibliographies we read); 50 citing papers with a page here →.

Updated

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