--- title: "Ziyang Huang — author profile and papers · Reasoning" description: "Ziyang Huang, Chinese Academy of Sciences: 2 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who…" canonical: "https://research.elamur.ai/free/en/authors/ziyang-huang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ziyang-huang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Ziyang Huang # Ziyang Huang Ziyang Huang has 2 papers in our library, in 2026, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Information retrieval & search](https://md.research.elamur.ai/free/en/topics/information-retrieval/); often with [Jun Zhao](https://md.research.elamur.ai/free/en/authors/jun-zhao/), [Kang Liu](https://md.research.elamur.ai/free/en/authors/kang-liu/), [Xiaowei Yuan](https://md.research.elamur.ai/free/en/authors/xiaowei-yuan/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139798866) · [**h-index 0**](https://openalex.org/authors/A5139798866) · [1 works](https://openalex.org/works?filter=author.id:A5139798866) · [0 citations](https://openalex.org/works?filter=author.id:A5139798866&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/ziyang-huang/#papers) · [⭐ Paper Stars ranking: #14151](https://md.research.elamur.ai/free/en/paper-stars/page/142/#star-14151) 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=Ziyang+Huang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ziyang+Huang) · [dblp](https://dblp.org/search?q=Ziyang+Huang) · [ACL Anthology](https://aclanthology.org/search/?q=Ziyang+Huang) ## Affiliations [🏛️**Chinese Academy of Sciences** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🔬**Institute of Automation** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/labs/institute-of-automation/) · [🎓**University of Chinese Academy of Sciences** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/university-of-chinese-academy-of-sciences/) 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 6 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/) · [Information Systems · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [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 2 Research subjects and languages the work is about.[Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/ziyang-huang/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Efficient Prior-Guided Reasoning for Robust Retrieval-Augmented Generation under Conflicts](https://md.research.elamur.ai/free/en/papers/yuan-2026-efficient-prior-guided-reasoning-robust/)** *(2026)* Retrieval-augmented generation (RAG) works well when the retrieved passages are clean. Accuracy drops sharply when the passages are noisy, outdated or contradict each other. The authors study whether a model's own knowledge can act as a reference point for judging such evidence. 2. **[R\textthreesuperiorA: Reinforced Reasoning for Relevance Assessment for RAG in User-Generated Content Platforms](https://md.research.elamur.ai/free/en/papers/yuan-2026-r-textthreesuperiora-reinforced-reasoning-relevance/)** *(2026)* The paper addresses query–document relevance judgment for retrieval-augmented generation on user-generated content (UGC) platforms. ## Co-authors here 8 co-authors with a page, the most papers together first. - [Jun Zhao](https://md.research.elamur.ai/free/en/authors/jun-zhao/) ×2 - [Kang Liu](https://md.research.elamur.ai/free/en/authors/kang-liu/) ×2 - [Xiaowei Yuan](https://md.research.elamur.ai/free/en/authors/xiaowei-yuan/) ×2 - [Yan Gao](https://md.research.elamur.ai/free/en/authors/yan-gao/) - [Yao Hu](https://md.research.elamur.ai/free/en/authors/yao-hu/) - [Yequan Wang](https://md.research.elamur.ai/free/en/authors/yequan-wang/) - [Yiwu](https://md.research.elamur.ai/free/en/authors/yiwu/) - [Zhao Yang](https://md.research.elamur.ai/free/en/authors/zhao-yang/) ## 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 Updated 2 November 2026