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Wenwei Zhang

Wenwei Zhang has 3 papers in our library, in 2023–2024, most of them on Vision & language; often with Bin Wang, Haodong Duan, Linke Ouyang.

3 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 25 · 105 works · 2,564 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 616 times in our library · 4 more in our library without a page yet · ⭐ Paper Stars ranking: #4474

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

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 12 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.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model (2024 · 92 citations)
    InternLM-XComposer2 is a vision-language model that both understands images and writes long documents mixing text and pictures. Its predecessor could only build such articles from a title. The new model accepts much richer inputs: outlines, detailed written requirements and reference images.
  2. InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition (2023 · 85 citations)
    Most open vision-language large models (VLLMs) produce only text. InternLM-XComposer, from Shanghai Artificial Intelligence Laboratory, extends this to writing long articles with illustrations placed inside the text, while also improving image understanding. The model pairs a visual encoder and a Perceive Sampler…
  3. Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Models (2024 · 63 citations)
    Open-source LLMs still perform much worse than API-based systems such as GPT-4 when used as agents. Tuning them on agent-specific data can also weaken their general skills. The authors make three diagnostic observations:

All works

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

  1. InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large ModelarXiv:2401.16420Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.2024 · 92 citations
  2. InternLM-Math: Open Math Large Language Models Toward Verifiable ReasoningarXiv:2402.06332 · original ↗ · no summary yetHuaiyuan Ying et al.2024 · 90 citations
  3. InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and CompositionarXiv:2309.15112Pan Zhang, Xiaoyi Dong, Bin Wang, et al.2023 · 85 citations
  4. InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HDarXiv:2404.06512 · original ↗ · no summary yetXiaoyi Dong et al.2024 · 52 citations
  5. InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and OutputarXiv:2407.03320 · original ↗ · no summary yetPan Zhang et al.2024 · 36 citations
  6. InternLM-Law: An Open Source Chinese Legal Large Language ModelarXiv:2406.14887 · original ↗ · no summary yetZhiwei Fei et al.2024 · 8 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 616 times (of the 141,840 papers whose bibliographies we read); 44 citing papers with a page here →.

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