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Can Chen

Can Chen has 2 papers in our library, in 2024–2025, most of them on Language models & pretraining, Information retrieval & search; often with Dong Li, Haolun Wu, Kaikai Song.

2 papers in our library · 2024–2025

OpenAlex · ORCID · h-index 29 · 181 works · 2,433 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 23 times in our library · ⭐ Paper Stars ranking: #6944

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

🎓University of North Carolina at Chapel HillChapel Hill · United States2024–2026 · 26 paperscurrent🎓Zhejiang UniversityHangzhou · China2016–2025 · 40 papers🏥Brigham and Women's HospitalBoston · United States2022–2024 · 10 papers🎓Harvard UniversityCambridge · United States2022–2024 · 10 papers🎓University of MichiganAnn Arbor · United States2019–2022 · 10 papers🎓National University of SingaporeSingapore · Singapore2010–2015 · 8 papers🎓Honghe UniversityWenlan · China2006–2013 · 8 papers🎓Huazhong University of Science and TechnologyWuhan · China2022–2025 · 7 papers🎓Zhejiang Ocean UniversityZhoushan · China2018–2020 · 7 papers🎓Northwest A&F UniversityYangling · China2015–2018 · 6 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 40 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 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 2Research subjects and languages the work is about.Information retrieval & search · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Retrieval-Augmented Generation for Natural Language Processing: A Survey (2024 · 86 citations)
    Large language models store knowledge implicitly in their weights. As a result, they can produce fluent but false answers, they need costly retraining to refresh facts, and they often lack depth in specialised domains. Retrieval-augmented generation (RAG) addresses these issues by consulting an external knowledge…
  2. Pangu Ultra: Pushing the Limits of Dense Large Language Models on Ascend NPUs (2025 · 6 citations)
    Pangu Ultra is Huawei's effort to show that a very deep dense Transformer, trained entirely on Ascend NPUs instead of GPUs, can compete with much larger sparse MoE systems.

 Co-authors here

12 of 14 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 23 times (of the 149,439 papers whose bibliographies we read); 8 citing papers with a page here →.

Updated

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