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Jinpeng Wang

Jinpeng Wang has 2 papers in our library, in 2023–2025, most of them on Language models & pretraining, Vision & language, Evaluation & benchmarks; often with Ji-Rong Wen, Kun Zhou, Yifan Du.

2 papers in our library · 2023–2025

OpenAlex · ORCID · h-index 20 · 94 works · 1,860 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 537 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #2455

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

🔬Beijing Automation Control Equipment InstituteBeijing · China2025–2026 · 2 paperscurrent🎓Harbin Institute of TechnologyHarbin · China2026 · 1 papercurrent🎓Sun Yat-sen UniversityGuangzhou · China2019–2022 · 19 papers🏢Microsoft Research AsiaBeijing · China2017–2021 · 15 papers🎓Tsinghua UniversityBeijing · China2021–2025 · 8 papers🎓National University of SingaporeSingapore · Singapore2022–2023 · 6 papers🎓Tsinghua Shenzhen International Graduate SchoolShenzhen · China2021–2025 · 5 papers🎓Liaoning Technical UniversityFuxin · China2024 · 4 papers🏢MeituanBeijing · China2021–2024 · 4 papers🏢TencentShenzhen · China2020–2024 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 19 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 3The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 works

🧭 Topics 4Research subjects and languages the work is about.Language models & pretraining · 2 worksVision & language · 2 worksEvaluation & benchmarks · 1 workReasoning · 1 work

 Works by year

2020s

20251 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Evaluating Object Hallucination in Large Vision-Language Models (2023 · 1,004 citations)
    The paper asks whether large vision-language models (LVLMs), which attach a strong LLM to a visual encoder, invent objects that are not in the image.
  2. What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Instruction Tuning (2025 · 13 citations)
    The paper asks which properties of visual instruction data actually help Multi-modal Large Language Models (MLLMs) generalize, since earlier collections had never been compared under the same backbone and training setup.

All works

4 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. Evaluating Object Hallucination in Large Vision-Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Yifan Li, Yifan Du, Kun Zhou, et al.2023 · 1,004 citations
  2. All in One: Exploring Unified Video-Language Pre-Training ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetJinpeng Wang et al.2023 · 180 citations
  3. A Simple Recipe towards Reducing Hallucination in Neural Surface Realisation ↗Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yetFeng Nie et al.2019 · 120 citations
  4. What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Instruction TuningInternational Conference on Computational Linguistics (COLING)Yifan Du, Hangyu Guo, Kun Zhou, et al.2025 · 13 citations

 Co-authors here

8 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 537 times (of the 149,439 papers whose bibliographies we read); 106 citing papers with a page here →.

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