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Qi Qian

Qi Qian has 2 papers in our library, in 2023, most of them on Language models & pretraining, Vision & language; often with Anwen Hu, Haiyang Xu, Ji Zhang.

2 papers in our library · 2023

OpenAlex · ORCID · Wikidata · h-index 20 · 55 works · 1,782 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 214 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #4364

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

🏢MetaMenlo Park · United States2026 · 1 papercurrent🏢Alibaba GroupHangzhou · China2019–2024 · 16 papers🏢Alibaba GroupSan Mateo · United States2016–2024 · 6 papers🎓Michigan State UniversityEast Lansing · United States2013–2015 · 5 papers🎓University of Washington TacomaTacoma · United States2019–2020 · 2 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.

 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).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

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

 Works by year

2020s

20232 papersQi Qian's papers of 2023

 Papers

The most cited first (OpenAlex and our library).

  1. mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration (2023 · 136 citations)
    Multi-modal LLMs usually take one of two routes. Some keep the language model frozen and feed it visual features through a Q-former or a linear projection, which limits how much the modalities can help each other. Others fine-tune the LLM on multi-modal instructions, which tends to weaken its text skills. mPLUG-Owl2…
  2. UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model (2023 · 128 citations)
    Understanding images that contain text, such as documents, tables, charts, webpages and street photos, usually requires either an external OCR system or costly domain-specific pretraining.

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. mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality CollaborationarXiv:2311.04257Qinghao Ye, Haiyang Xu, Jiabo Ye, et al.2023 · 136 citations
  2. UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language ModelFindings of the Association for Computational LinguisticsJiabo Ye, Anwen Hu, Haiyang Xu, et al.2023 · 128 citations
  3. mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models ↗arXiv:2408.04840 · no summary yetJiabo Ye et al.2024 · 57 citations

 Co-authors here

12 of 13 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 214 times (of the 141,840 papers whose bibliographies we read); 22 citing papers with a page here →.

Updated

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