--- title: "Haonan Dong · Peking University — author profile and papers" description: "Haonan Dong, Peking University: 2 papers on Elamur Research (2026), h-index 1 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/haonan-dong/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/haonan-dong/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Haonan Dong # Haonan Dong Haonan Dong has 2 papers in our library, in 2026, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Guojie Song](https://md.research.elamur.ai/free/en/authors/guojie-song/), [Kehan Jiang](https://md.research.elamur.ai/free/en/authors/kehan-jiang/), [Zhaolu Kang](https://md.research.elamur.ai/free/en/authors/zhaolu-kang/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5124386036) · [**h-index 1**](https://openalex.org/authors/A5124386036) · [6 works](https://openalex.org/works?filter=author.id:A5124386036) · [1 citations](https://openalex.org/works?filter=author.id:A5124386036&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/haonan-dong/#papers) · [🔗 Cited 28 times in our library](https://md.research.elamur.ai/free/en/authors/haonan-dong/cited-by/) · [⭐ Paper Stars ranking: #8580](https://md.research.elamur.ai/free/en/paper-stars/page/86/#star-8580) 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=Haonan+Dong) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Haonan+Dong) · [dblp](https://dblp.org/search?q=Haonan+Dong) · [ACL Anthology](https://aclanthology.org/search/?q=Haonan+Dong) ## Affiliations [🎓**Peking University** Beijing · China 2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/universities/peking-university/) · [🎓**Beijing Electronic Science and Technology Institute** Beijing · China 2026 · 1 paper*current*](https://ror.org/01xdzh226) 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 5 The field of science this work belongs to (OpenAlex fields).[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/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 1 Research subjects and languages the work is about.[Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/haonan-dong/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[FoE: Forest of Errors Makes the First Solution the Best in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/jiang-2026-foe-forest-errors-makes-first/)** *(2026 · 15 citations)* Large Reasoning Models such as DeepSeek-R1 often produce several alternative solutions inside a single chain of thought. 2. **[NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-Neurons](https://md.research.elamur.ai/free/en/papers/dong-2026-neureasoner-explainable-controllable-unified-reasoning/)** *(2026 · 13 citations)* Large Reasoning Models still make three kinds of mistakes. Within a step, they get calculations or derivations wrong. Across steps, they loop or stall. At the instance level, they over-think easy questions. Earlier fixes target only one of these, rely on opaque RL training, and offer little insight or control. ## Co-authors here 5 co-authors with a page, the most papers together first. - [Guojie Song](https://md.research.elamur.ai/free/en/authors/guojie-song/) ×2 - [Kehan Jiang](https://md.research.elamur.ai/free/en/authors/kehan-jiang/) ×2 - [Zhaolu Kang](https://md.research.elamur.ai/free/en/authors/zhaolu-kang/) ×2 - [Haoran Ye](https://md.research.elamur.ai/free/en/authors/haoran-ye/) - [Wenhao Zhu](https://md.research.elamur.ai/free/en/authors/wenhao-zhu/) ## 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/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×2 ## Cited by Papers of our library cite their works 28 times (of the 149,439 papers whose bibliographies we read); [9 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/haonan-dong/cited-by/). Updated 30 October 2026