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Zhonghang Li

Zhonghang Li has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning; often with Chao Huang, Jiabin Tang, Lianghao Xia.

2 papers in our library · 2025–2026

OpenAlex · ORCID · Wikidata · h-index 6 · 13 works · 400 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 52 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #10020

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 University of TechnologyGuangzhou · China2022–2026 · 7 paperscurrent🎓University of Hong KongPok Fu Lam · China2024–2026 · 5 paperscurrent

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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer 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

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. AI-Researcher: Autonomous Scientific Innovation (2025 · 40 citations)
    Large language models now handle coding and mathematical reasoning well, but turning these skills into a system that does original research on its own is still unsolved.
  2. LightReasoner: Can Small Language Models Teach Large Language Models Reasoning? (2026 · 1 citation)
    Standard supervised fine-tuning for reasoning is expensive. It typically uses rejection sampling against ground-truth answers and then updates every token equally, even though most tokens are routine. LightReasoner addresses this by letting a weaker "Amateur" model help train a stronger "Expert" model. At each step…

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. UrbanGPT: Spatio-Temporal Large Language Models ↗ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · no summary yetZhonghang Li et al.2024 · 189 citations
  2. AI-Researcher: Autonomous Scientific InnovationConference on Neural Information Processing Systems (NeurIPS)Jiabin Tang, Lianghao Xia, Zhonghang Li, et al.2025 · 40 citations
  3. LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?Annual Meeting of the Association for Computational Linguistics (ACL)Jingyuan Wang, Yankai Chen, Zhonghang Li, et al.2026 · 1 citation

 Co-authors here

4 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 52 times (of the 149,439 papers whose bibliographies we read); 17 citing papers with a page here →.

Updated

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