--- title: "Zhongwei Wan · Alibaba Group — author profile and papers" description: "Zhongwei Wan, Alibaba Group: 3 papers on Elamur Research (2023–2025), h-index 9 — affiliations, topics, co-authors and who cites them in…" canonical: "https://research.elamur.ai/free/en/authors/zhongwei-wan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhongwei-wan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zhongwei Wan # Zhongwei Wan Zhongwei Wan has 3 papers in our library, in 2023–2025, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Che Liu](https://md.research.elamur.ai/free/en/authors/che-liu/), [Chaofan Tao](https://md.research.elamur.ai/free/en/authors/chaofan-tao/), [Daniel Rueckert](https://md.research.elamur.ai/free/en/authors/daniel-rueckert/). 3 papers in our library · 2023–2025 [OpenAlex](https://openalex.org/A5061473466) · [ORCID](https://orcid.org/0000-0002-2790-0290) · [**h-index 9**](https://openalex.org/authors/A5061473466) · [73 works](https://openalex.org/works?filter=author.id:A5061473466) · [303 citations](https://openalex.org/works?filter=author.id:A5061473466&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/zhongwei-wan/#papers) · [🔗 Cited 140 times in our library](https://md.research.elamur.ai/free/en/authors/zhongwei-wan/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6870](https://md.research.elamur.ai/free/en/paper-stars/page/69/#star-6870) 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=Zhongwei+Wan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zhongwei+Wan) · [dblp](https://dblp.org/search?q=Zhongwei+Wan) · [ACL Anthology](https://aclanthology.org/search/?q=Zhongwei+Wan) ## Affiliations [🎓**The Ohio State University** Columbus · United States 2023–2026 · 46 papers*current*](https://md.research.elamur.ai/free/en/universities/the-ohio-state-university/) · [🏢**Alibaba Group** Hangzhou · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/alibaba-group/) · [🎓**University of Chinese Academy of Sciences** Beijing · China 2022–2023 · 3 papers](https://md.research.elamur.ai/free/en/universities/university-of-chinese-academy-of-sciences/) · [🏛️**Chinese Academy of Sciences** Beijing · China 2022 · 2 papers](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🔬**Shenzhen Institutes of Advanced Technology** Shenzhen · China 2022 · 2 papers](https://md.research.elamur.ai/free/en/labs/shenzhen-institutes-of-advanced-technology/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 7 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Vision and Pattern Recognition · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Medicine · 1 work](https://md.research.elamur.ai/free/en/shelves/medicine/) · [Health Informatics · 1 work](https://md.research.elamur.ai/free/en/shelves/medicine/health-informatics/) 🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) 💡 Concepts 1 Key ideas and methods explained on our concept pages.[Scaling laws · 1 work](https://md.research.elamur.ai/free/en/concepts/scaling-laws/) ## Works by year ### 2020s [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/zhongwei-wan/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/zhongwei-wan/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/zhongwei-wan/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[Efficient Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)** *(2023 · 110 citations)* Training and running LLMs with billions of parameters is costly. Using LLaMA data, the authors show that training compute rises steeply with model size while inference throughput falls. This survey maps research on cutting these costs and limits itself to techniques for billion-scale models rather than smaller… 2. **[Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies](https://md.research.elamur.ai/free/en/papers/tao-2024-scaling-laws-vocabulary-larger-models/)** *(2024 · 46 citations)* Standard scaling laws for LLMs predict loss from parameter count and training data but treat vocabulary size as fixed. 3. **[Beyond Distillation: Pushing the Limits of Medical LLM Reasoning with Minimalist Rule-Based RL](https://md.research.elamur.ai/free/en/papers/liu-2025-distillation-pushing-limits-medical-llm/)** *(2025 · 10 citations)* Medical LLMs usually learn to reason through supervised fine-tuning on chain-of-thought (CoT) traces, often distilled from proprietary systems such as GPT-4o. ## 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. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/) 2. [**Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies arXiv:2407.13623**Chaofan Tao, Qian Liu, Longxu Dou, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/tao-2024-scaling-laws-vocabulary-larger-models/) 3. [**Beyond Distillation: Pushing the Limits of Medical LLM Reasoning with Minimalist Rule-Based RL arXiv:2505.17952**Che Liu, Haozhe Wang, Jiazhen Pan, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-distillation-pushing-limits-medical-llm/) 4. **[DGLF: A Dual Graph-based Learning Framework for Multi-modal Sarcasm Detection ↗](https://aclanthology.org/2024.emnlp-main.170/) Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing · no summary yet**Zhihong Zhu et al.*2024 · 9 citations* ## Co-authors here 12 of 19 co-authors with a page, the most papers together first. - [Che Liu](https://md.research.elamur.ai/free/en/authors/che-liu/) ×2 - [Chaofan Tao](https://md.research.elamur.ai/free/en/authors/chaofan-tao/) - [Daniel Rueckert](https://md.research.elamur.ai/free/en/authors/daniel-rueckert/) - [Haozhe Wang](https://md.research.elamur.ai/free/en/authors/haozhe-wang/) - [Jiachen Liu](https://md.research.elamur.ai/free/en/authors/jiachen-liu/) - [Jiazhen Pan](https://md.research.elamur.ai/free/en/authors/jiazhen-pan/) - [Longxu Dou](https://md.research.elamur.ai/free/en/authors/longxu-dou/) - [Mi Zhang](https://md.research.elamur.ai/free/en/authors/mi-zhang/) - [Min Lin](https://md.research.elamur.ai/free/en/authors/min-lin/) - [Mosharaf Chowdhury](https://md.research.elamur.ai/free/en/authors/mosharaf-chowdhury/) - [Ngai Wong](https://md.research.elamur.ai/free/en/authors/ngai-wong/) - [Niklas Muennighoff](https://md.research.elamur.ai/free/en/authors/niklas-muennighoff/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing ## Cited by Papers of our library cite their works 140 times (of the 149,439 papers whose bibliographies we read); [32 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/zhongwei-wan/cited-by/). Updated 2 November 2026