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Haiteng Zhao

Haiteng Zhao has 3 papers in our library, in 2025–2026, most of them on Reasoning, Language models & pretraining; often with Fangzhi Xu, Hang Yan, Jun Liu.

3 papers in our library · 2025–2026

OpenAlex · h-index 5 · 24 works · 107 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 18 times in our library · ⭐ Paper Stars ranking: #10488

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 · China2022–2025 · 12 papers🏥Shanghai Children's Medical CenterShanghai · China2005–2022 · 4 papers🔬Shanghai Artificial Intelligence LaboratoryShanghai · China2025 · 3 papers🎓Shanghai Jiao Tong UniversityShanghai · China2020–2022 · 3 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).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 workApplied Mathematics · 1 workMathematics · 1 work

🧭 Topics 2Research subjects and languages the work is about.Reasoning · 3 worksLanguage models & pretraining · 1 work

 Works by year

2020s

20261 paper20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. MUR: Momentum Uncertainty guided Reasoning for Large Language Models (2026 · 8 citations)
    Test-time scaling (TTS) makes LLMs reason better but tends to cause overthinking: extra compute goes to every reasoning step, including trivial ones.
  2. Genius: A Generalizable and Purely Unsupervised Self-Training Framework For Advanced Reasoning (2025 · 8 citations)
    Genius tackles the problem of improving LLM reasoning after pre-training without any external supervision.
  3. Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving (2025 · 1 citation)
    Even strong Large Reasoning Models (LRMs) struggle on IMO-level problems. The exploration these problems need outgrows a single 64K–128K context window, and earlier workarounds were mostly prompt-only pipelines on proprietary models. The authors present Intern-S1-MO, an agent framework that splits problem solving…

 Co-authors here

12 of 21 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 18 times (of the 149,439 papers whose bibliographies we read); 13 citing papers with a page here →.

Updated

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