--- title: "Nan Cheng · China Mobile — author profile and papers" description: "Nan Cheng, China Mobile: 2 papers on Elamur Research (2025–2026), h-index 3 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/nan-cheng/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/nan-cheng/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Nan Cheng # Nan Cheng Nan Cheng has 2 papers in our library, in 2025–2026, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Feng Chen](https://md.research.elamur.ai/free/en/authors/feng-chen/), [Surya Ganguli](https://md.research.elamur.ai/free/en/authors/surya-ganguli/), [Yang Deng](https://md.research.elamur.ai/free/en/authors/yang-deng/). 2 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5111656480) · [**h-index 3**](https://openalex.org/authors/A5111656480) · [10 works](https://openalex.org/works?filter=author.id:A5111656480) · [16 citations](https://openalex.org/works?filter=author.id:A5111656480&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/nan-cheng/#papers) · [🔗 Cited 9 times in our library](https://md.research.elamur.ai/free/en/authors/nan-cheng/cited-by/) · [⭐ Paper Stars ranking: #12056](https://md.research.elamur.ai/free/en/paper-stars/page/121/#star-12056) 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=Nan+Cheng) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Nan+Cheng) · [dblp](https://dblp.org/search?q=Nan+Cheng) · [ACL Anthology](https://aclanthology.org/search/?q=Nan+Cheng) ## Affiliations [🏢**China Mobile Group Design Institute Co., Ltd.** Beijing · China 2009–2026 · 9 papers*current*](https://ror.org/05vp29s52) · [🏢**China Mobile** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/china-mobile/) 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/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 1 Research subjects and languages the work is about.[Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/nan-cheng/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/nan-cheng/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[Rethinking Fine-Tuning when Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2025-rethinking-fine-tuning-scaling-test/)** *(2025 · 9 citations)* Test-time strategies such as pass@N let a model try N times while a verifier checks each attempt. Fine-tuning, however, usually ignores this. The authors ask whether standard supervised fine-tuning with cross-entropy (CE) loss suits such strategies. 2. **[Hierarchical Reinforcement Learning with Augmented Step-Level Transitions for LLM Agents](https://md.research.elamur.ai/free/en/papers/zhen-2026-hierarchical-reinforcement-learning-augmented-step/)** *(2026 · 1 citation)* LLM agents that solve multi-step interactive tasks usually feed the model the entire, ever-growing record of past observations and actions. ## Co-authors here 4 co-authors with a page, the most papers together first. - [Feng Chen](https://md.research.elamur.ai/free/en/authors/feng-chen/) - [Surya Ganguli](https://md.research.elamur.ai/free/en/authors/surya-ganguli/) - [Yang Deng](https://md.research.elamur.ai/free/en/authors/yang-deng/) - [Yanhua Yu](https://md.research.elamur.ai/free/en/authors/yanhua-yu/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) - [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/): [NeurIPS 2025](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2025/) ## Cited by Papers of our library cite their works 9 times (of the 149,439 papers whose bibliographies we read); [3 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/nan-cheng/cited-by/). Updated 3 November 2026