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Zun Wang

Zun Wang has 3 papers in our library, in 2022–2024, most of them on Language models & pretraining, Vision & language, Evaluation & benchmarks; often with Guo Chen, Jilan Xu, Kunchang Li.

3 papers in our library · 2022–2024

OpenAlex · ORCID · h-index 11 · 35 works · 879 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 243 times in our library · ⭐ Paper Stars ranking: #2532

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

🎓Dalian University of TechnologyDalian · China2019–2025 · 7 paperscurrent🎓University of North Carolina at Chapel HillChapel Hill · United States2024–2025 · 3 paperscurrent🔬Shanghai Artificial Intelligence LaboratoryShanghai · China2022–2024 · 7 papers🎓Australian National UniversityCanberra · Australia2022–2023 · 5 papers🔬China Industrial Control Systems Cyber Emergency Response TeamBeijing2022–2024 · 2 papers🎓Jiangnan UniversityWuxi · China2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 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 3The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksComputer Vision and Pattern Recognition · 3 worksArtificial Intelligence · 2 works

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 2 worksVision & language · 2 worksEvaluation & benchmarks · 1 work

 Works by year

2020s

20241 paperInternVideo2: Scaling Foundation Models for Multimodal Video Understanding20231 paperMVBench: A Comprehensive Multi-modal Video Understanding Benchmark20221 paperInternVideo: General Video Foundation Models via Generative and Discriminative Learning

 Papers

The most cited first (OpenAlex and our library).

  1. MVBench: A Comprehensive Multi-modal Video Understanding Benchmark (2023 · 442 citations)
    Most existing evaluation suites for multi-modal large language models (MLLMs) test what a model sees in a single still image.
  2. InternVideo2: Scaling Foundation Models for Multimodal Video Understanding (2024 · 239 citations)
    InternVideo2 is a family of video foundation models from OpenGVLab (Shanghai AI Laboratory) with Nanjing University and SIAT-CAS.
  3. InternVideo: General Video Foundation Models via Generative and Discriminative Learning (2022 · 128 citations)
    Most vision foundation models are pretrained and adapted at the image level. This makes them a poor fit for video tasks, which depend on motion and temporal structure. Existing video models also tend to specialize in either action understanding or video-language tasks. InternVideo is a family of general-purpose video…

 Co-authors here

12 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 243 times (of the 141,840 papers whose bibliographies we read); 22 citing papers with a page here →.

Updated

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