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Peng Cheng

Peng Cheng has 2 papers in our library, in 2024–2026, most of them on Language models & pretraining; often with Biye Li, Bo Zhu, Cheng Cheng.

2 papers in our library · 2024–2026

OpenAlex · ORCID · h-index 20 · 95 works · 2,175 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 20 times in our library · ⭐ Paper Stars ranking: #8954

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓University of FloridaGainesville · United States2023–2026 · 13 paperscurrent🎓University of Florida HealthGainesville · United States2024–2026 · 4 paperscurrent🎓Xidian UniversityXi'an · China2018–2022 · 11 papers🎓Naval University of EngineeringWuhan · China2009–2023 · 10 papers🎓Peking UniversityBeijing · China2010–2020 · 5 papers🏢MicrosoftRedmond · United States2019–2025 · 4 papers🏢Guangzhou Automobile GroupGuangzhou · China2024–2025 · 3 papers🎓La Trobe UniversityMelbourne · Australia2022–2023 · 3 papers🏛️Chinese Academy of SciencesBeijing · China2016–2025 · 2 papers🎓Huazhong University of Science and TechnologyWuhan · China2014–2023 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 29 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models (2024 · 21 citations)
    Training sparse Mixture-of-Experts (MoE) LLMs involves several practical choices whose effects are poorly understood.
  2. Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training (2026 · 1 citation)
    Continual pre-training of an LLM on a narrow target field, such as math, often causes catastrophic forgetting of general skills.

 Co-authors here

12 of 17 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 20 times (of the 149,439 papers whose bibliographies we read); 4 citing papers with a page here →.

Updated

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