---
title: "Weiran He — author profile and papers — Elamur Research"
description: "Weiran He, Moonshot AI: 2 papers on Elamur Research (2024–2025), h-index 2 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/weiran-he/"
---
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# Weiran He

Weiran He has 2 papers in our library, in 2024–2025, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Enzhe Lu](https://md.research.elamur.ai/free/en/authors/enzhe-lu/), [Weimin Zheng](https://md.research.elamur.ai/free/en/authors/weimin-zheng/), [Xinran Xu](https://md.research.elamur.ai/free/en/authors/xinran-xu/).

2 papers in our library · 2024–2025

[OpenAlex](https://openalex.org/A5108325909) · [ORCID](https://orcid.org/0009-0009-7951-6854) · [Wikidata](https://www.wikidata.org/wiki/Q141675013) · [**h-index 2**](https://openalex.org/authors/A5108325909) · [2 works](https://openalex.org/works?filter=author.id:A5108325909) · [39 citations](https://openalex.org/works?filter=author.id:A5108325909&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/weiran-he/#papers) · [🔗 Cited 201 times in our library](https://md.research.elamur.ai/free/en/authors/weiran-he/cited-by/) · [⭐ Paper Stars ranking: #6051](https://md.research.elamur.ai/free/en/paper-stars/page/61/#star-6051)

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=Weiran+He) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Weiran+He) · [dblp](https://dblp.org/search?q=Weiran+He) · [ACL Anthology](https://aclanthology.org/search/?q=Weiran+He)

## Affiliations

[🏢**Moonshot AI** Beijing · China 2025 · 2 papers*current*](https://md.research.elamur.ai/free/en/companies/moonshot-ai/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

## 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 · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Networks and Communications · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-networks-and-communications/) · [Hardware and Architecture · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/hardware-and-architecture/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Artificial Intelligence · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/)

🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/)

## Works by year

### 2020s

[**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/weiran-he/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/weiran-he/year/2024/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving](https://md.research.elamur.ai/free/en/papers/qin-2024-mooncake-kvcache-centric-disaggregated-architecture/)** *(2024 · 161 citations)* Mooncake is the production serving system behind Kimi, Moonshot AI's LLM service. It tackles a constrained optimization problem: maximize useful throughput while still meeting latency targets for time to first token (TTFT) and time between tokens (TBT), and do so under frequent heavy overload. The design runs prefill…
2. **[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.

## Co-authors here

4 co-authors with a page, the most papers together first.

- [Enzhe Lu](https://md.research.elamur.ai/free/en/authors/enzhe-lu/)
- [Weimin Zheng](https://md.research.elamur.ai/free/en/authors/weimin-zheng/)
- [Xinran Xu](https://md.research.elamur.ai/free/en/authors/xinran-xu/)
- [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/)
- FAST 2025

## Cited by

Papers of our library cite their works 201 times (of the 149,439 papers whose bibliographies we read); [20 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/weiran-he/cited-by/).

Updated 2 November 2026
