--- title: "Enzhe Lu — author profile and papers — Elamur Research" description: "Enzhe Lu: 2 papers on Elamur Research (2025), h-index 4 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/enzhe-lu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/enzhe-lu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Enzhe Lu # Enzhe Lu Enzhe Lu has 2 papers in our library, in 2025, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Jiaxi Hu](https://md.research.elamur.ai/free/en/authors/jiaxi-hu/), [Kimi Team](https://md.research.elamur.ai/free/en/authors/kimi-team/), [Xin Men](https://md.research.elamur.ai/free/en/authors/xin-men/). 2 papers in our library · 2025 [OpenAlex](https://openalex.org/A5049660040) · [**h-index 4**](https://openalex.org/authors/A5049660040) · [7 works](https://openalex.org/works?filter=author.id:A5049660040) · [180 citations](https://openalex.org/works?filter=author.id:A5049660040&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/enzhe-lu/#papers) · [🔗 Cited 688 times in our library](https://md.research.elamur.ai/free/en/authors/enzhe-lu/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6428](https://md.research.elamur.ai/free/en/paper-stars/page/65/#star-6428) 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=Enzhe+Lu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Enzhe+Lu) · [dblp](https://dblp.org/search?q=Enzhe+Lu) · [ACL Anthology](https://aclanthology.org/search/?q=Enzhe+Lu) ## Affiliations [🏛️**Guangzhou Center for Disease Control and Prevention** Guangzhou · China 2006–2020 · 2 papers](https://ror.org/007jnt575) 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 5 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [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/) · [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.[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/) ## Works by year ### 2020s [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/enzhe-lu/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[MoBA: Mixture of Block Attention for Long-Context LLMs](https://md.research.elamur.ai/free/en/papers/lu-2025-moba-mixture-block-attention/)** *(2025 · 80 citations)* Standard softmax attention grows quadratically with sequence length, which makes long-context LLMs expensive to train and run. 2. **[Kimi Linear: An Expressive, Efficient Attention Architecture](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-linear-expressive-efficient/)** *(2025 · 51 citations)* Softmax attention becomes a bottleneck for agentic and RL-heavy LLM workloads. Its cost grows quadratically with sequence length, and its KV cache keeps expanding during long decoding. Earlier linear-attention and hybrid designs saved compute but usually lost quality or were only tested at small scale. The Kimi Team… ## All works 3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them. 1. **[Muon is Scalable for LLM Training ↗](https://arxiv.org/abs/2502.16982) arXiv:2502.16982 · no summary yet**Jingyuan Liu et al.*2025 · 83 citations* 2. **[MoBA: Mixture of Block Attention for Long-Context LLMs](https://md.research.elamur.ai/free/en/papers/lu-2025-moba-mixture-block-attention/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Enzhe Lu, Zhejun Jiang, Jingyuan Liu, et al.*2025 · 80 citations* 3. [**Kimi Linear: An Expressive, Efficient Attention Architecture arXiv:2510.26692**Kimi Team, Yu Zhang, Zongyu Lin, et al.*2025 · 51 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-linear-expressive-efficient/) ## Co-authors here 6 co-authors with a page, the most papers together first. - [Jiaxi Hu](https://md.research.elamur.ai/free/en/authors/jiaxi-hu/) - [Kimi Team](https://md.research.elamur.ai/free/en/authors/kimi-team/) - [Xin Men](https://md.research.elamur.ai/free/en/authors/xin-men/) - [Xingcheng Yao](https://md.research.elamur.ai/free/en/authors/xingcheng-yao/) - [Yu Zhang](https://md.research.elamur.ai/free/en/authors/yu-zhang/) - [Zhiqi Huang](https://md.research.elamur.ai/free/en/authors/zhiqi-huang/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/): [NeurIPS 2025](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2025/) ## Cited by Papers of our library cite their works 688 times (of the 149,439 papers whose bibliographies we read); [174 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/enzhe-lu/cited-by/). Updated 30 October 2026