--- title: "Zhengze Zhou — author profile and papers · Reasoning" description: "Zhengze Zhou, LinkedIn: 2 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/zhengze-zhou/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhengze-zhou/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zhengze Zhou # Zhengze Zhou Zhengze Zhou has 2 papers in our library, in 2026, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Hejian Sang](https://md.research.elamur.ai/free/en/authors/hejian-sang/), [Ran He](https://md.research.elamur.ai/free/en/authors/ran-he/), [Yuanda Xu](https://md.research.elamur.ai/free/en/authors/yuanda-xu/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5125510945) · [**h-index 0**](https://openalex.org/authors/A5125510945) · [11 works](https://openalex.org/works?filter=author.id:A5125510945) · [0 citations](https://openalex.org/works?filter=author.id:A5125510945&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/zhengze-zhou/#papers) · [🔗 Cited 34 times in our library](https://md.research.elamur.ai/free/en/authors/zhengze-zhou/cited-by/) · [⭐ Paper Stars ranking: #10296](https://md.research.elamur.ai/free/en/paper-stars/page/103/#star-10296) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Zhengze+Zhou) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zhengze+Zhou) · [dblp](https://dblp.org/search?q=Zhengze+Zhou) · [ACL Anthology](https://aclanthology.org/search/?q=Zhengze+Zhou) ## Affiliations [🎓**Cornell University** Ithaca · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/cornell-university/) · [🏢**LinkedIn** Sunnyvale · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/linkedin/) 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 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 2 Research subjects and languages the work is about.[Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/zhengze-zhou/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[CRISP: Compressed Reasoning via Iterative Self-Policy Distillation](https://md.research.elamur.ai/free/en/papers/sang-2026-crisp-compressed-reasoning-iterative-self/)** *(2026 · 17 citations)* Reasoning models often produce very long chains of thought, even for simple problems. This raises inference cost and can introduce mistakes. CRISP shortens reasoning without labelled answers, length budgets or difficulty estimators. The model acts as its own teacher: the same network, given an extra instruction to be… 2. **[TIP: Token Importance in On-Policy Distillation](https://md.research.elamur.ai/free/en/papers/xu-2026-tip-token-importance-policy-distillation/)** *(2026 · 17 citations)* On-policy distillation (OPD) trains a student model on sequences it generates itself, with the teacher giving feedback at every token. ## Co-authors here 5 co-authors with a page, the most papers together first. - [Hejian Sang](https://md.research.elamur.ai/free/en/authors/hejian-sang/) ×2 - [Ran He](https://md.research.elamur.ai/free/en/authors/ran-he/) ×2 - [Yuanda Xu](https://md.research.elamur.ai/free/en/authors/yuanda-xu/) ×2 - [Zhipeng Wang](https://md.research.elamur.ai/free/en/authors/zhipeng-wang/) ×2 - [Alborz Geramifard](https://md.research.elamur.ai/free/en/authors/alborz-geramifard/) ## Cited by Papers of our library cite their works 34 times (of the 149,439 papers whose bibliographies we read); [4 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/zhengze-zhou/cited-by/). Updated 3 November 2026