--- title: "Hao Feng — author profile and papers — Elamur Research" description: "Hao Feng, University of Science and Technology of China: 2 papers on Elamur Research (2025–2026), h-index 44 — affiliations, topics…" canonical: "https://research.elamur.ai/free/en/authors/hao-feng/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/hao-feng/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Hao Feng # Hao Feng Hao Feng has 2 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [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 [Haiyang Yu](https://md.research.elamur.ai/free/en/authors/haiyang-yu/), [Han Wang](https://md.research.elamur.ai/free/en/authors/han-wang/), [Jinghui Lu](https://md.research.elamur.ai/free/en/authors/jinghui-lu/). 2 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5005177314) · [ORCID](https://orcid.org/0000-0002-0899-0438) · [**h-index 44**](https://openalex.org/authors/A5005177314) · [277 works](https://openalex.org/works?filter=author.id:A5005177314) · [6,127 citations](https://openalex.org/works?filter=author.id:A5005177314&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/hao-feng/#papers) · [🔗 Cited 12 times in our library](https://md.research.elamur.ai/free/en/authors/hao-feng/cited-by/) · [⭐ Paper Stars ranking: #9695](https://md.research.elamur.ai/free/en/paper-stars/page/97/#star-9695) 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=Hao+Feng) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Hao+Feng) · [dblp](https://dblp.org/search?q=Hao+Feng) · [ACL Anthology](https://aclanthology.org/search/?q=Hao+Feng) ## Affiliations [🎓**Northeastern University** Shenyang · China 2012–2026 · 167 papers*current*](https://md.research.elamur.ai/free/en/universities/northeastern-university-cn/) · [🎓**University of Science and Technology of China** Hefei · China 2023–2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-science-and-technology-of-china/) · [🎓**Shaanxi University of Science and Technology** Xi'an · China 2022–2026 · 3 papers*current*](https://ror.org/034t3zs45) · [🏛️**Chinese Academy of Sciences** Beijing · China 2017–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🔬**Institute of Metal Research** Shenyang · China 2017–2026 · 2 papers*current*](https://ror.org/03pa1rf77) · [🎓**Nanjing University of Science and Technology** Nanjing · China 2022–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/nanjing-university-of-science-and-technology/) · [🔬**Shenyang National Laboratory for Materials Science** Shenyang · China 2021–2026 · 2 papers*current*](https://ror.org/05nkvrx25) · [🏢**Intel** Santa Clara · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/intel/) · [🎓**Northeastern University** Boston · United States 2012–2025 · 20 papers](https://md.research.elamur.ai/free/en/universities/northeastern-university/) · [🎓**Taiyuan University of Technology** Taiyuan · China 2019–2025 · 14 papers](https://ror.org/03kv08d37) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 34 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 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/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/hao-feng/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/hao-feng/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[Prolonged Reasoning Is Not All You Need: Certainty-Based Adaptive Routing for Efficient LLM/MLLM Reasoning](https://md.research.elamur.ai/free/en/papers/lu-2025-prolonged-reasoning-all-need-certainty/)** *(2025 · 11 citations)* Reasoning-tuned LLMs and MLLMs tend to produce long chain-of-thought output for every query. This costs many tokens and can even hurt accuracy on easy, fact-based questions. A pilot with Qwen2.5-0.5B on text-rich VQA and KIE data showed that direct answers were both more accurate and far cheaper than reasoning-based… 2. **[From Local to Global: Revisiting Structured Pruning Paradigms for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-local-global-revisiting-structured-pruning/)** *(2026 · 1 citation)* Most structured pruning methods for LLMs work locally. They rebuild each layer's outputs separately from calibration data. This keeps perplexity and generic zero-shot behaviour reasonable, but it does not tie the pruning to a downstream task, so task-specific calibration data adds little. The authors return to global… ## Co-authors here 7 co-authors with a page, the most papers together first. - [Haiyang Yu](https://md.research.elamur.ai/free/en/authors/haiyang-yu/) - [Han Wang](https://md.research.elamur.ai/free/en/authors/han-wang/) - [Jinghui Lu](https://md.research.elamur.ai/free/en/authors/jinghui-lu/) - [Jingqun Tang](https://md.research.elamur.ai/free/en/authors/jingqun-tang/) - [Li Yang](https://md.research.elamur.ai/free/en/authors/li-yang/) - [Siliang Xu](https://md.research.elamur.ai/free/en/authors/siliang-xu/) - [Ziyan Wang](https://md.research.elamur.ai/free/en/authors/ziyan-wang/) ## 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/) ## Cited by Papers of our library cite their works 12 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/hao-feng/cited-by/). Updated 1 November 2026