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Jiazhan Feng

Jiazhan Feng has 3 papers in our library, in 2023–2025, most of them on Language models & pretraining, Reasoning; often with Shijue Huang, Wanjun Zhong, Can Xu.

3 papers in our library · 2023–2025

OpenAlex · ORCID · Wikidata · h-index 8 · 44 works · 291 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 807 times in our library · ⭐ Paper Stars ranking: #3006

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

🎓Peking UniversityBeijing · China2019–2026 · 28 paperscurrent

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 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksComputer Science · 3 worksArts and Humanities · 2 worksLanguage and Linguistics · 2 works

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

 Works by year

2020s

20252 papers20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. WizardLM: Empowering large pre-trained language models to follow complex instructions (2023 · 741 citations)
    Open-domain instruction data written by people is costly to collect, and it contains few truly hard instructions.
  2. ReTool: Reinforcement Learning for Strategic Tool Use in LLMs (2025 · 88 citations)
    RL-trained reasoning LLMs handle verbal reasoning well but often make mistakes on exact arithmetic, equation solving and symbolic manipulation. A code interpreter can do these steps reliably. ReTool, from ByteDance Seed, trains a model to decide on its own when and how to call such an interpreter while it reasons.
  3. UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning (2025 · 26 citations)
    UI-TARS-2 (ByteDance Seed) is a native GUI agent: a single end-to-end policy that perceives, reasons, remembers and acts across desktops, phones, browsers and games.

 Co-authors here

12 of 22 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 807 times (of the 149,439 papers whose bibliographies we read); 254 citing papers with a page here →.

Updated

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