--- title: "Dong Du — author profile and papers — Elamur Research" description: "Dong Du: 3 papers on Elamur Research (2024–2026), h-index 0 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/dong-du/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/dong-du/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Dong Du # Dong Du Dong Du has 3 papers in our library, in 2024–2026, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Ao Liu](https://md.research.elamur.ai/free/en/authors/ao-liu/), [Botong Zhou](https://md.research.elamur.ai/free/en/authors/botong-zhou/), [Can Xu](https://md.research.elamur.ai/free/en/authors/can-xu/). 3 papers in our library · 2024–2026 [OpenAlex](https://openalex.org/A5152610636) · [**h-index 0**](https://openalex.org/authors/A5152610636) · [1 works](https://openalex.org/works?filter=author.id:A5152610636) · [0 citations](https://openalex.org/works?filter=author.id:A5152610636&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/dong-du/#papers) · [🔗 Cited 36 times in our library](https://md.research.elamur.ai/free/en/authors/dong-du/cited-by/) · [⭐ Paper Stars ranking: #8229](https://md.research.elamur.ai/free/en/paper-stars/page/83/#star-8229) 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+Du) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Dong+Du) · [dblp](https://dblp.org/search?q=Dong+Du) · [ACL Anthology](https://aclanthology.org/search/?q=Dong+Du) ## 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 · 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/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 2 Research subjects and languages the work is about.[Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/dong-du/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/dong-du/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/dong-du/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[HunyuanProver: A Scalable Data Synthesis Framework and Guided Tree Search for Automated Theorem Proving](https://md.research.elamur.ai/free/en/papers/li-2024-hunyuanprover-scalable-data-synthesis/)** *(2024 · 25 citations)* Formal theorem proving in LEAN4 remains difficult for language models. The search space is enormous, and there is little supervised data: mathlib4 provides only about 50k theorems with tactics. HunyuanProver addresses this by fine-tuning the Hunyuan 7B model with two components. The first is a low-cost, iterative… 2. **[Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/team-2025-hunyuan-hunyuan-turbos-advancing-large/)** *(2025 · 10 citations)* Hunyuan-TurboS tackles the tension between strong LLM quality and inference cost, especially for long inputs and reasoning-heavy requests. 3. **[Hunyuan-A13B Technical Report](https://md.research.elamur.ai/free/en/papers/team-2026-hunyuan-hunyuan-a13b-technical-report/)** *(2026 · 1 citation)* Serving frontier LLMs is costly because dense models use every weight for every token. Tencent's Hunyuan team addresses this with Hunyuan-A13B, an openly released sparse Mixture-of-Experts model. It has 80B parameters in total, but only about 13B are active per token: one always-on shared expert plus 8 of 64… ## Co-authors here 12 of 17 co-authors with a page, the most papers together first. - [Ao Liu](https://md.research.elamur.ai/free/en/authors/ao-liu/) ×2 - [Botong Zhou](https://md.research.elamur.ai/free/en/authors/botong-zhou/) ×2 - [Can Xu](https://md.research.elamur.ai/free/en/authors/can-xu/) ×2 - [Chayse Zhou](https://md.research.elamur.ai/free/en/authors/chayse-zhou/) ×2 - [ChenChen Zhang](https://md.research.elamur.ai/free/en/authors/chenchen-zhang/) ×2 - [Chengcheng Xu](https://md.research.elamur.ai/free/en/authors/chengcheng-xu/) ×2 - [Chenhao Wang](https://md.research.elamur.ai/free/en/authors/chenhao-wang/) ×2 - [Decheng Wu](https://md.research.elamur.ai/free/en/authors/decheng-wu/) ×2 - [Dengpeng Wu](https://md.research.elamur.ai/free/en/authors/dengpeng-wu/) ×2 - [Dian Jiao](https://md.research.elamur.ai/free/en/authors/dian-jiao/) ×2 - [Tencent Hunyuan Team](https://md.research.elamur.ai/free/en/authors/tencent-hunyuan-team/) ×2 - [Chen Li](https://md.research.elamur.ai/free/en/authors/chen-li/) ## Cited by Papers of our library cite their works 36 times (of the 149,439 papers whose bibliographies we read); [8 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/dong-du/cited-by/). Updated 31 October 2026