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Wenjun Gao

Wenjun Gao has 2 papers in our library, in 2024, most of them on Reasoning, GPU & parallel computing; often with Qiushi Du, Bo Liu, Chengqi Deng.

2 papers in our library · 2024

OpenAlex · ORCID · Wikidata · h-index 6 · 17 works · 1,975 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 244 times in our library · ⭐ Paper Stars ranking: #6203

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

🎓Second Military Medical UniversityShanghai · China2012–2026 · 6 paperscurrent🏢DeepSeekHangzhou · China2025 · 2 papers🏥Second Affiliated Hospital of Zhejiang UniversityHangzhou · China2025 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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).Computer Science · 2 worksArtificial Intelligence · 1 workComputational Theory and Mathematics · 1 workMathematics · 1 workComputer Networks and Communications · 1 workHardware and Architecture · 1 workInformation Systems · 1 work

🧭 Topics 2Research subjects and languages the work is about.Reasoning · 1 workGPU & parallel computing · 1 work

 Works by year

2020s

20242 papers

 Papers

The most cited first (OpenAlex and our library).

  1. DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search (2024 · 116 citations)
    Language models still struggle with formal theorem proving in Lean 4. When a model writes a whole proof in one go, it never sees the intermediate proof states, so one early mistake can derail everything that follows. DeepSeek-Prover-V1.5 is an open 7B model that addresses this through staged training and a new search…
  2. Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning (2024 · 34 citations)
    Compute and bandwidth needs for deep learning, especially LLMs, are rising much faster than hardware improves. Fast chips and interconnects make large clusters costly to build and run. DeepSeek-AI presents Fire-Flyer AI-HPC, a combined hardware and software design for building such infrastructure cheaply.

 Co-authors here

12 of 13 co-authors with a page, the most papers together first.

 Cited by

Papers of our library cite their works 244 times (of the 149,439 papers whose bibliographies we read); 31 citing papers with a page here →.

Updated

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