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Ziyang Zhang

Ziyang Zhang has 2 papers in our library, in 2025; often with Fangcheng Liu, George Michalopoulos, Hang Zhou.

2 papers in our library · 2025

OpenAlex · ORCID · h-index 12 · 55 works · 768 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 20 times in our library · ⭐ Paper Stars ranking: #11137

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

🏛️Chinese Academy of SciencesBeijing · China2002–2026 · 9 paperscurrent🎓University of Chinese Academy of SciencesBeijing · China2024–2026 · 4 paperscurrent🎓Nanjing Tech UniversityNanjing · China2025–2026 · 2 paperscurrent🎓Shandong UniversityJinan · China2026 · 1 papercurrent🔬Shanghai Institute of Materia MedicaPudong · China2026 · 1 papercurrent🔬State Key Laboratory of Drug ResearchShanghai2026 · 1 papercurrent🎓Kyoto Institute of TechnologyKyoto · Japan2014–2016 · 16 papers🎓Kitami Institute of TechnologyKitami · Japan2012–2014 · 4 papers🔬Shanghai Institute of Microsystem and Information TechnologyShanghai · China2024 · 3 papers🔬Suzhou Institute of Nano-tech and Nano-bionicsSuzhou · China2017–2018 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 14 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 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 workComputer Vision and Pattern Recognition · 1 workHardware and Architecture · 1 work

 Works by year

2020s

20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. LMR-BENCH: Evaluating LLM Agent's Ability on Reproducing Language Modeling Research (2025 · 12 citations)
    LLM agents are increasingly used for research work, but it is unclear whether they can turn the methods in a published NLP paper into working code inside a real codebase.
  2. Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs (2025 · 8 citations)
    Training MoE language models with nearly a trillion parameters is hard: the hardware is underused because the set of experts each token activates changes at runtime, and the scale strains communication and memory.

 Co-authors here

12 of 15 co-authors with a page, the most papers together first.

 Cited by

Papers of our library cite their works 20 times (of the 149,439 papers whose bibliographies we read); 7 citing papers with a page here →.

Updated

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