--- title: "Dong Li · Beijing Tongren Hospital — author profile and papers" description: "Dong Li, Beijing Tongren Hospital: 6 papers on Elamur Research (2021–2025), h-index 27 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/dong-li/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/dong-li/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Dong Li # Dong Li Dong Li has 6 papers in our library, in 2021–2025, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Kaikai Song](https://md.research.elamur.ai/free/en/authors/kaikai-song/), [Weigao Sun](https://md.research.elamur.ai/free/en/authors/weigao-sun/), [Weixuan Sun](https://md.research.elamur.ai/free/en/authors/weixuan-sun/). 6 papers in our library · 2021–2025 [OpenAlex](https://openalex.org/A5069055892) · [ORCID](https://orcid.org/0000-0003-0120-5756) · [Wikidata](https://www.wikidata.org/wiki/Q96644957) · [**h-index 27**](https://openalex.org/authors/A5069055892) · [176 works](https://openalex.org/works?filter=author.id:A5069055892) · [2,967 citations](https://openalex.org/works?filter=author.id:A5069055892&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/dong-li/#papers) · [🔗 Cited 378 times in our library](https://md.research.elamur.ai/free/en/authors/dong-li/cited-by/) · [⭐ Paper Stars ranking: #4108](https://md.research.elamur.ai/free/en/paper-stars/page/42/#star-4108) 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=Dong+Li) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Dong+Li) · [dblp](https://dblp.org/search?q=Dong+Li) · [ACL Anthology](https://aclanthology.org/search/?q=Dong+Li) ## Affiliations [🎓**Capital Medical University** Beijing · China 2009–2026 · 98 papers*current*](https://ror.org/013xs5b60) · [🏥**Beijing Tongren Hospital** Beijing · China 2016–2026 · 79 papers*current*](https://ror.org/013e4n276) · [🏛️**Ministry of Industry and Information Technology** Beijing · China 2020–2026 · 54 papers*current*](https://ror.org/0385nmy68) · [🏥**Beijing Anzhen Hospital** Beijing · China 2009–2025 · 15 papers](https://ror.org/02h2j1586) · [🏥**Tianjin Medical University General Hospital** Tianjin · China 2008–2025 · 9 papers](https://ror.org/003sav965) · [🏥**First Affiliated Hospital of Harbin Medical University** Harbin · China 2012–2022 · 8 papers](https://ror.org/05vy2sc54) · [🎓**Harbin Medical University** Harbin · China 2012–2022 · 8 papers](https://ror.org/05jscf583) · [🤝**The Lundquist Institute** Torrance · United States 2013–2022 · 7 papers](https://ror.org/025j2nd68) · [🎓**Tianjin Medical University** Tianjin · China 2008–2025 · 6 papers](https://ror.org/02mh8wx89) · [🏥**Harbor–UCLA Medical Center** Torrance · United States 2014–2023 · 6 papers](https://ror.org/05h4zj272) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 30 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 6 The field of science this work belongs to (OpenAlex fields).[Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Vision and Pattern Recognition · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Hardware and Architecture · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/hardware-and-architecture/) 🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 5 works](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2025** 3 papers](https://md.research.elamur.ai/free/en/authors/dong-li/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/dong-li/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/dong-li/year/2023/) · [**2021** 1 paper](https://md.research.elamur.ai/free/en/authors/dong-li/year/2021/) ## Papers The most cited first (OpenAlex and our library). 1. **[ZeRO-Offload: Democratizing Billion-Scale Model Training](https://md.research.elamur.ai/free/en/papers/ren-2021-zero-offload-democratizing-billion-scale/)** *(2021 · 309 citations)* Training models with billions of parameters usually needs many GPUs, because existing parallel methods only work when the combined GPU memory can hold the parameters, gradients and optimizer states. 2. **[MiniMax-01: Scaling Foundation Models with Lightning Attention](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-01-scaling-foundation/)** *(2025 · 50 citations)* Most current LLMs and VLMs handle 32K–256K tokens of context. That is often too little for tasks like reading whole books, working across entire code repositories, or many-shot in-context learning. The main obstacle is that softmax attention cost grows quadratically with length. MiniMax-01 addresses this with a… 3. **[TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer](https://md.research.elamur.ai/free/en/papers/qin-2023-transnormerllm-faster-better-large/)** *(2023 · 33 citations)* Linear attention promises to remove the quadratic cost of softmax attention. In practice, earlier linear-attention models have trailed Transformers in language-modeling quality and rarely ran faster on real hardware. The authors close this gap with TransNormerLLM, a redesigned version of their TransNormer… 4. **[Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models](https://md.research.elamur.ai/free/en/papers/qin-2024-lightning-attention-2-free/)** *(2024 · 31 citations)* Linear attention should cost O(n) instead of the O(n²) of softmax attention. In causal language modeling, however, existing implementations lose this advantage: the kernel trick needs a cumulative summation (cumsum) that parallelizes poorly on GPUs. Lightning Attention-1 had already reduced the memory-I/O bottleneck… 5. **[Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition](https://md.research.elamur.ai/free/en/papers/chen-2025-pangu-embedded-efficient-dual/)** *(2025 · 13 citations)* Reasoning-focused LLMs such as DeepSeek-R1 are expensive to deploy because they are very large and generate long chains of thought, sometimes tens of thousands of tokens per problem. 6. **[Pangu Ultra: Pushing the Limits of Dense Large Language Models on Ascend NPUs](https://md.research.elamur.ai/free/en/papers/yin-2025-pangu-ultra-pushing-limits/)** *(2025 · 6 citations)* Pangu Ultra is Huawei's effort to show that a very deep dense Transformer, trained entirely on Ascend NPUs instead of GPUs, can compete with much larger sparse MoE systems. ## Co-authors here 12 of 38 co-authors with a page, the most papers together first. - [Kaikai Song](https://md.research.elamur.ai/free/en/authors/kaikai-song/) ×2 - [Weigao Sun](https://md.research.elamur.ai/free/en/authors/weigao-sun/) ×2 - [Weixuan Sun](https://md.research.elamur.ai/free/en/authors/weixuan-sun/) ×2 - [Xuyang Shen](https://md.research.elamur.ai/free/en/authors/xuyang-shen/) ×2 - [Yasheng Wang](https://md.research.elamur.ai/free/en/authors/yasheng-wang/) ×2 - [Yiran Zhong](https://md.research.elamur.ai/free/en/authors/yiran-zhong/) ×2 - [Zhen Qin](https://md.research.elamur.ai/free/en/authors/zhen-qin/) ×2 - [Aonian Li](https://md.research.elamur.ai/free/en/authors/aonian-li/) - [Bangwei Gong](https://md.research.elamur.ai/free/en/authors/bangwei-gong/) - [Bin Wang](https://md.research.elamur.ai/free/en/authors/bin-wang/) - [Bo Yang](https://md.research.elamur.ai/free/en/authors/bo-yang/) - [Boji Shan](https://md.research.elamur.ai/free/en/authors/boji-shan/) ## Cited by Papers of our library cite their works 378 times (of the 149,439 papers whose bibliographies we read); [53 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/dong-li/cited-by/). Updated 30 October 2026