--- title: "Yibo Zhu — author profile and papers — Elamur Research" description: "Yibo Zhu, StepFun AI: 2 papers on Elamur Research (2022–2024), h-index 32 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/yibo-zhu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yibo-zhu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yibo Zhu # Yibo Zhu Yibo Zhu has 2 papers in our library, in 2022–2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Cong Wang](https://md.research.elamur.ai/free/en/authors/cong-wang/), [Hao Zhang](https://md.research.elamur.ai/free/en/authors/hao-zhang/), [Shengyu Liu](https://md.research.elamur.ai/free/en/authors/shengyu-liu/). 2 papers in our library · 2022–2024 [OpenAlex](https://openalex.org/A5028120333) · [ORCID](https://orcid.org/0000-0002-9113-2660) · [Wikidata](https://www.wikidata.org/wiki/Q130970963) · [**h-index 32**](https://openalex.org/authors/A5028120333) · [106 works](https://openalex.org/works?filter=author.id:A5028120333) · [4,396 citations](https://openalex.org/works?filter=author.id:A5028120333&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yibo-zhu/#papers) · [🔗 Cited 533 times in our library](https://md.research.elamur.ai/free/en/authors/yibo-zhu/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #4248](https://md.research.elamur.ai/free/en/paper-stars/page/43/#star-4248) 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=Yibo+Zhu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yibo+Zhu) · [dblp](https://dblp.org/search?q=Yibo+Zhu) · [ACL Anthology](https://aclanthology.org/search/?q=Yibo+Zhu) ## Affiliations [🏢**StepFun AI** Shanghai · China 2024–2026 · 10 papers*current*](https://md.research.elamur.ai/free/en/companies/stepfun-ai/) · [🎓**University of Connecticut** Storrs · United States 2010–2016 · 27 papers](https://md.research.elamur.ai/free/en/universities/university-of-connecticut/) · [🏢**ByteDance** Beijing · China 2018–2024 · 17 papersEmployment since 2018](https://md.research.elamur.ai/free/en/companies/bytedance/) · [🎓**University of California, Santa Barbara** Santa Barbara · United States 2011–2016 · 13 papersEducation 2011–2016](https://md.research.elamur.ai/free/en/universities/university-of-california-santa-barbara/) · [🏢**Microsoft** Redmond · United States 2016–2019 · 11 papers](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🏢**Google** Mountain View · United States 2023–2024 · 2 papers](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**Xi'an Jiaotong University** Xi'an · China 2008–2009 · 2 papers](https://md.research.elamur.ai/free/en/universities/xi-an-jiaotong-university/) · [🎓**Tsinghua University** Beijing · China 2007–2011Education 2007–2011](https://md.research.elamur.ai/free/en/universities/tsinghua-university/) 🏛️**ByteDance Inc.** Bellevue · [United States](https://md.research.elamur.ai/free/en/countries/united-states/) Employment From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 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 7 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/) · [Hardware and Architecture · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/hardware-and-architecture/) · [Information Systems · 2 works](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/) · [Language and Linguistics · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/yibo-zhu/year/2024/) · [**2022** 1 paper](https://md.research.elamur.ai/free/en/authors/yibo-zhu/year/2022/) ## Papers The most cited first (OpenAlex and our library). 1. **[DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving](https://md.research.elamur.ai/free/en/papers/zhong-2024-distserve-disaggregating-prefill-decoding-goodput/)** *(2024 · 409 citations)* LLM inference has two phases with different profiles. Prefill processes the whole prompt in one compute-heavy step. Decoding emits one token per step and is bound by memory bandwidth. Mainstream systems batch both phases on the same GPUs. As a result, prefill delays inflate TPOT, decoding work inflates TTFT, and both… 2. **[Accelerating Distributed MoE Training and Inference with Lina](https://md.research.elamur.ai/free/en/papers/li-2022-accelerating-distributed-moe-training-inference/)** *(2022 · 92 citations)* Mixture-of-Experts (MoE) models keep per-token compute low by sending each token to only one or two expert FFNs. ## 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. [**DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving OSDI 2024**Yinmin Zhong, Shengyu Liu, Junda Chen, et al.*2024 · 409 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-distserve-disaggregating-prefill-decoding-goodput/) 2. [**Accelerating Distributed MoE Training and Inference with Lina arXiv:2210.17223**Jiamin Li, Yimin Jiang, Yibo Zhu, et al.*2022 · 92 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-accelerating-distributed-moe-training-inference/) 3. **[Efficient Long-context Language Model Training by Core Attention Disaggregation ↗](https://arxiv.org/abs/2510.18121) arXiv:2510.18121 · no summary yet**Yonghao Zhuang et al.*2025 · 1 citation* ## Co-authors here 6 co-authors with a page, the most papers together first. - [Cong Wang](https://md.research.elamur.ai/free/en/authors/cong-wang/) - [Hao Zhang](https://md.research.elamur.ai/free/en/authors/hao-zhang/) - [Shengyu Liu](https://md.research.elamur.ai/free/en/authors/shengyu-liu/) - [Xin Jin](https://md.research.elamur.ai/free/en/authors/xin-jin/) - [Xuanzhe Liu](https://md.research.elamur.ai/free/en/authors/xuanzhe-liu/) - [Yinmin Zhong](https://md.research.elamur.ai/free/en/authors/yinmin-zhong/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - OSDI 2024 ## Cited by Papers of our library cite their works 533 times (of the 149,439 papers whose bibliographies we read); [34 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yibo-zhu/cited-by/). Updated 2 November 2026