🧑‍🔬 Wanrong Zhu

🏛️ Affiliations

🏢Adobe SystemsSan Jose · United States2024–2026 · 7 paperscurrent🎓University of California, IrvineIrvine · United States2024–2026 · 4 paperscurrent🎓University of ChicagoChicago · United States2020–2026 · 4 paperscurrent🎓Irvine UniversityCerritos · United States2026 · 1 papercurrent🎓University of California, Santa BarbaraSanta Barbara · United States2019–2024 · 15 papersEducation 2019–2024 · PhD, Computer Science🎓University of California, Santa CruzSanta Cruz · United States2020–2023 · 6 papers🎓University of California San DiegoSan Diego · United States2020–2022 · 3 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.

🧭 Fields, topics and concepts

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

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models (2023 · 222 citations)
   Strong autoregressive vision-language models like DeepMind's Flamingo accept mixed sequences of images and text, which allows in-context learning from a few demonstrations.
2. Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning (2023 · 116 citations)
   In-context learning in LLMs depends heavily on which few-shot demonstrations are chosen. Existing theories of why it works have mostly been tested on synthetic data and toy Transformers. This paper treats real-world LLMs as implicit latent variable models, similar to topic models. In this view, the prompt lets the…
3. MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific Understanding (2024 · 20 citations)
   Large Vision Language Models (LVLMs) are increasingly pitched as research assistants, but existing benchmarks mostly test simple charts or figures from a narrow set of fields.

All works

4 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. OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language ModelsarXiv:2308.01390Anas Awadalla, Irena Gao, Josh Gardner, et al.2023 · 222 citations
2. Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Xinyi Wang, Wanrong Zhu, Michael Saxon, et al.2023 · 116 citations
3. Multimodal Text Style Transfer for Outdoor Vision-and-Language Navigation ↗Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume · no summary yetWanrong Zhu et al.2021 · 40 citations
4. MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific UnderstandingarXiv:2407.04903Zekun Li, Xianjun Yang, Kyuri Choi, et al.2024 · 20 citations

🤝 Co-authors here

11 co-authors with a page, the most papers together first.

• Jack Hessel
• Jenia Jitsev
• Michael Saxon
• Samir Yitzhak Gadre
• Simon Kornblith
• William Yang Wang
• Xianjun Yang
• Xifeng Yan
• Xinyi Wang
• Yonatan Bitton
• Zekun Li

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Conference on Neural Information Processing Systems (NeurIPS): NeurIPS 2023
• Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

🔗 Cited by

Papers of our library cite their works 267 times (of the 149,439 papers whose bibliographies we read); 49 citing papers with a page here →.

Updated 1 November 2026

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