--- title: "Da Zheng — author profile and papers — Elamur Research" description: "Da Zheng, Hefei University of Technology: 4 papers on Elamur Research (2025–2026), h-index 9 — affiliations, topics, co-authors and who…" canonical: "https://research.elamur.ai/free/en/authors/da-zheng/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/da-zheng/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Da Zheng # Da Zheng Da Zheng has 4 papers in our library, in 2025–2026, 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/), [Knowledge graphs & ontologies](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/); often with [Huajun Chen](https://md.research.elamur.ai/free/en/authors/huajun-chen/), [Ningyu Zhang](https://md.research.elamur.ai/free/en/authors/ningyu-zhang/), [Lun Du](https://md.research.elamur.ai/free/en/authors/lun-du/). 4 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5101155301) · [**h-index 9**](https://openalex.org/authors/A5101155301) · [66 works](https://openalex.org/works?filter=author.id:A5101155301) · [193 citations](https://openalex.org/works?filter=author.id:A5101155301&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/da-zheng/#papers) · [🔗 Cited 55 times in our library](https://md.research.elamur.ai/free/en/authors/da-zheng/cited-by/) · [⭐ Paper Stars ranking: #8711](https://md.research.elamur.ai/free/en/paper-stars/page/88/#star-8711) 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=Da+Zheng) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Da+Zheng) · [dblp](https://dblp.org/search?q=Da+Zheng) · [ACL Anthology](https://aclanthology.org/search/?q=Da+Zheng) ## Affiliations [🎓**Hefei University of Technology** Hefei · China 2023–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/hefei-university-of-technology/) · [🔬**Research Institute of Petroleum Exploration and Development** Beijing · China 2022–2023 · 4 papers](https://ror.org/02awe6g05) · [🏢**Amazon** Seattle · United States 2021–2022 · 3 papers](https://md.research.elamur.ai/free/en/companies/amazon/) · [🎓**Southeast University** Nanjing · China 2006–2015 · 3 papers](https://md.research.elamur.ai/free/en/universities/southeast-university-cn/) · [🎓**Chengdu University of Technology** Chengdu · China 2011–2024 · 2 papers](https://ror.org/05pejbw21) · [🎓**Johns Hopkins University** Baltimore · United States 2014–2022 · 2 papers](https://md.research.elamur.ai/free/en/universities/johns-hopkins-university/) · [🔬**State Key Laboratory of Digital Medical Engineering** Nanjing · China 2006–2007 · 2 papers](https://ror.org/03ab0at74) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 18 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 8 The field of science this work belongs to (OpenAlex fields).[Computer Science · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 4 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/) · [Decision Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Information Systems and Management · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/information-systems-and-management/) 🧭 Topics 4 Research subjects and languages the work is about.[Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Knowledge graphs & ontologies · 1 work](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/da-zheng/year/2026/) · [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/da-zheng/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[LightThinker: Thinking Step-by-Step Compression](https://md.research.elamur.ai/free/en/papers/zhang-2025-lightthinker-thinking-step-step-compression/)** *(2025 · 50 citations)* Slow, o1-style reasoning makes LLMs produce very long token sequences. Because attention cost grows quadratically and the KV Cache grows linearly with context, these outputs are expensive in memory and time. LightThinker addresses this by teaching a model to condense each intermediate reasoning step as it goes. After… 2. **[Untie the Knots: An Efficient Data Augmentation Strategy for Long-Context Pre-Training in Language Models](https://md.research.elamur.ai/free/en/papers/tian-2025-untie-knots-efficient-data-augmentation/)** *(2025 · 7 citations)* Extending large language models to very long contexts is difficult for three reasons. Natural documents of 32K–128K tokens are scarce. Upsampling long data shifts the training distribution and can hurt short-context skills. Attention over long sequences is also expensive. The authors propose Untie the Knots (UtK), an… 3. **[KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality](https://md.research.elamur.ai/free/en/papers/ren-2026-knowrl-exploring-knowledgeable-reinforcement-learning/)** *(2026 · 5 citations)* Slow-thinking LLMs such as DeepSeek-R1 distillations reason well but hallucinate heavily. One reason is that standard RL rewards only the final answer, so invented reasoning steps still get reinforced whenever the answer happens to be right. KnowRL addresses this by adding factual supervision to the reasoning trace… 4. **[What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations](https://md.research.elamur.ai/free/en/papers/luo-2026-what-makes-ai-research-replicable/)** *(2026)* LLM agents that try to reproduce AI papers often fail to produce working code. Papers leave out implementation specifics, and standard RAG does not recover technical details buried in cited works or the code signals in related repositories. The authors propose Executable Knowledge Graphs (xKG), a plug-in knowledge… ## Co-authors here 12 co-authors with a page, the most papers together first. - [Huajun Chen](https://md.research.elamur.ai/free/en/authors/huajun-chen/) ×3 - [Ningyu Zhang](https://md.research.elamur.ai/free/en/authors/ningyu-zhang/) ×3 - [Lun Du](https://md.research.elamur.ai/free/en/authors/lun-du/) ×2 - [Shuofei Qiao](https://md.research.elamur.ai/free/en/authors/shuofei-qiao/) ×2 - [Yujie Luo](https://md.research.elamur.ai/free/en/authors/yujie-luo/) ×2 - [Yuqi Zhu](https://md.research.elamur.ai/free/en/authors/yuqi-zhu/) ×2 - [Debing Zhang](https://md.research.elamur.ai/free/en/authors/debing-zhang/) - [Jintian Zhang](https://md.research.elamur.ai/free/en/authors/jintian-zhang/) - [Junfeng Tian](https://md.research.elamur.ai/free/en/authors/junfeng-tian/) - [Mengshu Sun](https://md.research.elamur.ai/free/en/authors/mengshu-sun/) - [Rui Wang](https://md.research.elamur.ai/free/en/authors/rui-wang/) - [Yang Chen](https://md.research.elamur.ai/free/en/authors/yang-chen/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) ×3: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×2, [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2025](https://md.research.elamur.ai/free/en/venues/emnlp/2025/) ## Cited by Papers of our library cite their works 55 times (of the 149,439 papers whose bibliographies we read); [27 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/da-zheng/cited-by/). Updated 2 November 2026