--- title: "Liangdong Wang — author profile and papers in our library" description: "Liangdong Wang, Beijing Academy of Artificial Intelligence: 2 papers on Elamur Research (2024), h-index 6 — affiliations, topics, co-authors…" canonical: "https://research.elamur.ai/free/en/authors/liangdong-wang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/liangdong-wang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Liangdong Wang # Liangdong Wang Liangdong Wang has 2 papers in our library, in 2024, most of them on [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Bo-Wen Zhang](https://md.research.elamur.ai/free/en/authors/bo-wen-zhang/), [Shuhao Gu](https://md.research.elamur.ai/free/en/authors/shuhao-gu/), [Yixuan Wang](https://md.research.elamur.ai/free/en/authors/yixuan-wang/). 2 papers in our library · 2024 [OpenAlex](https://openalex.org/A5017706182) · [**h-index 6**](https://openalex.org/authors/A5017706182) · [22 works](https://openalex.org/works?filter=author.id:A5017706182) · [228 citations](https://openalex.org/works?filter=author.id:A5017706182&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/liangdong-wang/#papers) · [🔗 Cited 14 times in our library](https://md.research.elamur.ai/free/en/authors/liangdong-wang/cited-by/) · [⭐ Paper Stars ranking: #9551](https://md.research.elamur.ai/free/en/paper-stars/page/96/#star-9551) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Liangdong+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Liangdong+Wang) · [dblp](https://dblp.org/search?q=Liangdong+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Liangdong+Wang) ## Affiliations [🔬**Beijing Academy of Artificial Intelligence** Beijing · China 2024–2026 · 6 papers*current*](https://md.research.elamur.ai/free/en/labs/beijing-academy-of-artificial-intelligence/) · [🎓**Zhejiang University** Hangzhou · China 2023–2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/universities/zhejiang-university/) · [🎓**Shantou University** Shantou · China 2023 · 2 papers](https://ror.org/01a099706) · [🎓**Shantou University Medical College** Shantou · China 2023 · 2 papers](https://ror.org/02gxych78) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 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 5 The field of science this work belongs to (OpenAlex fields).[Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Arts and Humanities · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 1 Research subjects and languages the work is about.[Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) ## Works by year ### 2020s [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/liangdong-wang/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[Infinity-MM: Scaling Multimodal Performance with Large-Scale and High-Quality Instruction Data](https://md.research.elamur.ai/free/en/papers/gu-2024-infinity-mm-scaling-multimodal-performance/)** *(2024 · 13 citations)* Open vision-language models (VLMs) trained only on public instruction data still trail systems built on proprietary data. 2. **[Aquila2 Technical Report](https://md.research.elamur.ai/free/en/papers/zhang-2024-aquila2-technical-report/)** *(2024 · 1 citation)* Most LLMs are pretrained on a fixed dataset over a long run, so it is hard to change the data mix or add new sources partway through. BAAI's Aquila2 is a family of Chinese–English bilingual models at 7B, 34B and an experimental 70B size. They were trained with HeuriMentor (HM), a framework with three parts: ## Co-authors here 4 co-authors with a page, the most papers together first. - [Bo-Wen Zhang](https://md.research.elamur.ai/free/en/authors/bo-wen-zhang/) ×2 - [Shuhao Gu](https://md.research.elamur.ai/free/en/authors/shuhao-gu/) ×2 - [Yixuan Wang](https://md.research.elamur.ai/free/en/authors/yixuan-wang/) - [Yulong Ao](https://md.research.elamur.ai/free/en/authors/yulong-ao/) ## Cited by Papers of our library cite their works 14 times (of the 149,439 papers whose bibliographies we read); [4 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/liangdong-wang/cited-by/). Updated 31 October 2026