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Chengyue Wu

Chengyue Wu has 2 papers in our library, in 2024, most of them on Vision & language, Language models & pretraining; often with Wen Liu, Xiaokang Chen, Xingchao Liu.

2 papers in our library · 2024

OpenAlex · ORCID · Wikidata · h-index 19 · 113 works · 1,078 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 172 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #4496

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

🎓The University of Texas at AustinAustin · United States2018–2026 · 60 paperscurrent🏥The University of Texas MD Anderson Cancer CenterHouston · United States2023–2026 · 21 paperscurrent🎓University of Hong KongPok Fu Lam · China2023–2025 · 9 papers🏢TencentShenzhen · China2023–2025 · 4 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 5The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 work

🧭 Topics 2Research subjects and languages the work is about.Vision & language · 2 worksLanguage models & pretraining · 1 work

 Works by year

2020s

20242 papersChengyue Wu's papers of 2024

 Papers

The most cited first (OpenAlex and our library).

  1. DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding (2024 · 135 citations)
    DeepSeek-VL2 is a family of open vision-language models. It pairs a sparse Mixture-of-Experts language backbone with a more flexible image encoder, with the goal of better multimodal quality without raising per-token compute. Its predecessor, DeepSeek-VL, worked only at fixed input resolutions, which hurt performance…
  2. Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation (2024 · 100 citations)
    Unified multimodal models such as Chameleon typically use one visual encoder for both image understanding and image generation.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal UnderstandingarXiv:2412.10302Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.2024 · 135 citations
  2. Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and GenerationIEEE Computer Society Conference on Computer Vision and Pattern RecognitionChengyue Wu, Xiaokang Chen, Zhiyu Wu, et al.2024 · 100 citations
  3. JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation ↗arXiv:2411.07975 · no summary yetYiyang Ma et al.2024 · 45 citations

 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 172 times (of the 141,840 papers whose bibliographies we read); 9 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/chengyue-wu/