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Yi Hu

Yi Hu has 2 papers in our library, in 2025, most of them on Reasoning, Language models & pretraining; often with Boyuan Chen, Chenyang Wang, Da Zheng.

2 papers in our library · 2025

OpenAlex · ORCID · h-index 24 · 114 works · 1,863 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 54 times in our library · ⭐ Paper Stars ranking: #9474

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

🎓Nanjing Tech UniversityNanjing · China2006–2026 · 65 paperscurrent🔬State Key Laboratory of Materials-Oriented Chemical EngineeringNanjing2009–2026 · 57 paperscurrent🎓Jiangxi Normal UniversityNanchang · China2011–2013 · 7 papers🤝Scripps Research InstituteSan Diego · United States2013–2016 · 4 papers🎓Beijing Jiaotong UniversityBeijing · China2025 · 2 papers🎓University of California San DiegoSan Diego · United States1997 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 19 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

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

 Works by year

2020s

20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems? (2025 · 37 citations)
    The paper asks whether enlarging the pool of long chain-of-thought (Long-CoT) training data yields stronger "slow-thinking" reasoners, and which factors matter most.
  2. PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models (2025 · 21 citations)
    Popular reasoning benchmarks for LLMs are nearly saturated, often built from public material that models may have seen in training, and sometimes contain faulty items or scoring rules.

 Co-authors here

11 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 54 times (of the 149,439 papers whose bibliographies we read); 22 citing papers with a page here →.

Updated

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