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Chengfeng Mao

Chengfeng Mao has 2 papers in our library, in 2020–2023, most of them on Language models & pretraining, Vision & language; often with AmirAli Bagher Zadeh, Ehsan Hoque, Louis-Philippe Morency.

2 papers in our library · 2020–2023

OpenAlex · ORCID · h-index 6 · 13 works · 867 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 117 citations in our library · ⭐ Paper Star rank #2494

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

🎓Massachusetts Institute of TechnologyCambridge · United States2018–2026 · 7 paperscurrent🎓Carnegie Mellon UniversityPittsburgh · United States2019–2025 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 7 Computer Science · 2 works Arts and Humanities · 1 work Artificial Intelligence · 2 works Computer Vision and Pattern Recognition · 2 works Language and Linguistics · 1 work Medicine · 1 work Health Informatics · 1 work

🧭 Topics 2 Vision & language · 1 work Language models & pretraining · 1 work

 Works by year

2020s

20231 paper20201 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Integrating Multimodal Information in Large Pretrained Transformers (2020 · 743 citations)
    Pretrained Transformers such as BERT and XLNet accept only text. Applying them to multimodal language, where spoken words come with voice and facial cues, has therefore meant one of two compromises: discarding the nonverbal signals, or using the models only to produce word features for a separate fusion network. The…
  2. A Survey of Large Language Models in Medicine: Progress, Application, and Challenge (2023 · 87 citations)
    This survey maps how large language models are being adapted to medicine. It covers how they are built, how well they perform, and what blocks their clinical use. Earlier reviews mostly described ChatGPT-style applications through small case studies. They offered little guidance on constructing medical models or…

 Co-authors here

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

 Cited by

Papers of our library cite their works 117 times (of the 141,840 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated

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