--- title: "Zheyuan Bai — author profile and papers — Elamur Research" description: "Zheyuan Bai: 2 papers on Elamur Research (2023–2024), h-index 2 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/zheyuan-bai/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zheyuan-bai/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zheyuan Bai # Zheyuan Bai Zheyuan Bai has 2 papers in our library, in 2023–2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Fangcheng Liu](https://md.research.elamur.ai/free/en/authors/fangcheng-liu/), [Kai Han](https://md.research.elamur.ai/free/en/authors/kai-han/), [Yehui Tang](https://md.research.elamur.ai/free/en/authors/yehui-tang/). 2 papers in our library · 2023–2024 [OpenAlex](https://openalex.org/A5112925827) · [**h-index 2**](https://openalex.org/authors/A5112925827) · [5 works](https://openalex.org/works?filter=author.id:A5112925827) · [93 citations](https://openalex.org/works?filter=author.id:A5112925827&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/zheyuan-bai/#papers) · [🔗 Cited 17 times in our library](https://md.research.elamur.ai/free/en/authors/zheyuan-bai/cited-by/) · [⭐ Paper Stars ranking: #10463](https://md.research.elamur.ai/free/en/paper-stars/page/105/#star-10463) 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=Zheyuan+Bai) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zheyuan+Bai) · [dblp](https://dblp.org/search?q=Zheyuan+Bai) · [ACL Anthology](https://aclanthology.org/search/?q=Zheyuan+Bai) ## Affiliations [🏢**Huawei Technologies** Shenzhen · China 2023 · 2 papers](https://md.research.elamur.ai/free/en/companies/huawei-technologies/) 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).[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/) · [Arts and Humanities · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [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 [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/zheyuan-bai/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/zheyuan-bai/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation](https://md.research.elamur.ai/free/en/papers/wang-2023-pangu-pi-enhancing-language/)** *(2023 · 10 citations)* Progress in large language models has mostly come from adding parameters and data. The design of the Transformer block itself gets little attention, even though large models are costly to run. The authors study LLaMA-style decoders and identify feature collapse: a rank metric shows token representations growing more… 2. **[PanGu-π Pro:Rethinking Optimization and Architecture for Tiny Language Models](https://md.research.elamur.ai/free/en/papers/tang-2024-pangu-pi-pro-rethinking/)** *(2024 · 8 citations)* On-device deployment needs small language models that still perform well. Most tiny models, however, simply reuse recipes designed for much larger LLMs, and few studies test which of those choices actually suit a ~1B-parameter model. The authors run a systematic set of ablations on a 1B LLaMA-style baseline, trained… ## Co-authors here 9 co-authors with a page, the most papers together first. - [Fangcheng Liu](https://md.research.elamur.ai/free/en/authors/fangcheng-liu/) ×2 - [Kai Han](https://md.research.elamur.ai/free/en/authors/kai-han/) ×2 - [Yehui Tang](https://md.research.elamur.ai/free/en/authors/yehui-tang/) ×2 - [Yunhe Wang](https://md.research.elamur.ai/free/en/authors/yunhe-wang/) ×2 - [Hanting Chen](https://md.research.elamur.ai/free/en/authors/hanting-chen/) - [Tianyu Guo](https://md.research.elamur.ai/free/en/authors/tianyu-guo/) - [Ying Nie](https://md.research.elamur.ai/free/en/authors/ying-nie/) - [Yun Wang](https://md.research.elamur.ai/free/en/authors/yun-wang/) - [Zhicheng Liu](https://md.research.elamur.ai/free/en/authors/zhicheng-liu/) ## Cited by Papers of our library cite their works 17 times (of the 149,439 papers whose bibliographies we read); [6 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/zheyuan-bai/cited-by/). Updated 2 November 2026