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Zulong Chen

Zulong Chen has 3 papers in our library, in 2023–2026, most of them on Reasoning, Language models & pretraining, Efficient models & compression; often with Liangyue Li, Chenglin Li, Defu Lian.

3 papers in our library · 2023–2026

OpenAlex · ORCID · Wikidata · h-index 9 · 58 works · 359 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 14 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9523

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

🏢Alibaba GroupHangzhou · China2020–2026 · 52 papersEmployment · Directorcurrent🎓Hangzhou Dianzi UniversityHangzhou · China2021–2026 · 2 paperscurrent🎓Fudan UniversityShanghai · China2024–2025 · 2 papers
🏛️Northeastern University Software CollegeShenyang · ChinaEducation · master

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6The 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 workInformation Systems · 1 work

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

 Works by year

2020s

20262 papers20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Mixed Distillation Helps Smaller Language Model Better Reasoning (2023 · 11 citations)
    Large language models reason well but are expensive to run. Earlier work on distilling reasoning into compact models mostly transfers only natural-language Chain of Thought (CoT). This paper argues that Program of Thought (PoT), where the model writes executable Python, is a valuable extra training signal. The…
  2. Long-Chain Reasoning Distillation via Adaptive Prefix Alignment (2026 · 3 citations)
    Small student models often learn poorly from the long, reflective chain-of-thought traces that reasoning models such as DeepSeek-R1 produce.
  3. Learning from Emptiness: De-biasing Listwise Rerankers with Content-Agnostic Probability Calibration (2026)
    Generative listwise rerankers built on LLMs suffer from position bias: their output depends on where a document sits in the prompt, not only on its relevance.

All works

4 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. Mixed Distillation Helps Smaller Language Model Better ReasoningarXiv:2312.10730Chenglin Li, Qianglong Chen, Liangyue Li, et al.2023 · 11 citations
  2. Long-Chain Reasoning Distillation via Adaptive Prefix AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Zhenghao Liu, Zhuoyang Wu, Xinze Li, et al.2026 · 3 citations
  3. Learning from Emptiness: De-biasing Listwise Rerankers with Content-Agnostic Probability CalibrationAnnual Meeting of the Association for Computational Linguistics (ACL)Hang Lv, Hongchao Gu, Ruiqing Yang, et al.2026
  4. Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetYuqi Xiong et al.2026

 Co-authors here

12 of 18 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 14 times (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

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