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Yufeng Yuan

Yufeng Yuan has 2 papers in our library, in 2025, most of them on Language models & pretraining, Reasoning; often with Lingjun Liu, Tiantian Fan, Xin Liu.

2 papers in our library · 2025

OpenAlex · ORCID · h-index 3 · 13 works · 112 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 742 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #2778

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

🎓South China Normal UniversityGuangzhou · China2022–2025 · 2 papers🎓Nanjing University of Science and TechnologyNanjing · China2022 · 2 papers🏢CloudwalkGuangzhou2019–2020 · 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.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksLanguage and Linguistics · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksMathematics · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20252 papersYufeng Yuan's papers of 2025

 Papers

The most cited first (OpenAlex and our library).

  1. DAPO: An Open-Source LLM Reinforcement Learning System at Scale (2025 · 634 citations)
    Reasoning-focused LLMs such as OpenAI o1 and DeepSeek R1 get much of their ability from large-scale reinforcement learning, but their reports leave out the training details that matter, so others have struggled to reproduce the results.
  2. Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning (2025 · 61 citations)
    Seed1.5-Thinking is a reasoning model from ByteDance Seed. It works through an extended chain of thought before giving its answer. The authors identify three factors behind strong reasoning models: training data, a stable RL algorithm and scalable RL infrastructure.

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. DAPO: An Open-Source LLM Reinforcement Learning System at ScalearXiv:2503.14476Qiying Yu, Zheng Zhang, Ruofei Zhu, et al.2025 · 634 citations
  2. VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning TasksarXiv:2504.05118 · original ↗ · no summary yetYu Yue et al.2025 · 65 citations
  3. Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement LearningarXiv:2504.13914ByteDance Seed, Jiaze Chen, Tiantian Fan, et al.2025 · 61 citations

 Co-authors here

8 co-authors with a page, the most papers together first.

 Cited by

Papers of our library cite their works 742 times (of the 141,840 papers whose bibliographies we read); 16 citing papers with a page here →.

Updated

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