--- title: "Zhixuan Yang — author profile and papers — Elamur Research" description: "Zhixuan Yang, Northeastern University: 2 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites them…" canonical: "https://research.elamur.ai/free/en/authors/zhixuan-yang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhixuan-yang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zhixuan Yang # Zhixuan Yang Zhixuan Yang has 2 papers in our library, in 2026, most of them on [Information extraction](https://md.research.elamur.ai/free/en/topics/information-extraction/); often with [Fu Zhang](https://md.research.elamur.ai/free/en/authors/fu-zhang/), [Huangming Xu](https://md.research.elamur.ai/free/en/authors/huangming-xu/), [Jingwei Cheng](https://md.research.elamur.ai/free/en/authors/jingwei-cheng/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139715843) · [ORCID](https://orcid.org/0009-0005-3583-4720) · [**h-index 0**](https://openalex.org/authors/A5139715843) · [3 works](https://openalex.org/works?filter=author.id:A5139715843) · [0 citations](https://openalex.org/works?filter=author.id:A5139715843&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/zhixuan-yang/#papers) · [⭐ Paper Stars ranking: #14134](https://md.research.elamur.ai/free/en/paper-stars/page/142/#star-14134) 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=Zhixuan+Yang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zhixuan+Yang) · [dblp](https://dblp.org/search?q=Zhixuan+Yang) · [ACL Anthology](https://aclanthology.org/search/?q=Zhixuan+Yang) ## Affiliations [🎓**Northeastern University** Shenyang · China 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/northeastern-university-cn/) 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).[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/) · [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.[Information extraction · 2 works](https://md.research.elamur.ai/free/en/topics/information-extraction/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/zhixuan-yang/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[ATGL: An Adaptive-Threshold Global Loss for Document-level Relation Extraction](https://md.research.elamur.ai/free/en/papers/xu-2026-atgl-adaptive-threshold-global-loss/)** *(2026)* The paper addresses a weakness in how document-level relation extraction (DocRE) models are trained. DocRE is a multi-label task, and most current systems use the Adaptive Threshold Loss (ATL) or its variants. These losses learn a per-pair threshold class TH but optimize positive and negative relations separately.… 2. **[DEBAR: Mitigating Contextual Bias in Cross-Document Relation Extraction via Dual-Stream Decoupling](https://md.research.elamur.ai/free/en/papers/yang-2026-debar-mitigating-contextual-bias-cross/)** *(2026)* Cross-document relation extraction (CodRE) predicts the relation between a head and a tail entity that appear in different documents, linked through shared bridge entities. ## Co-authors here 4 co-authors with a page, the most papers together first. - [Fu Zhang](https://md.research.elamur.ai/free/en/authors/fu-zhang/) ×2 - [Huangming Xu](https://md.research.elamur.ai/free/en/authors/huangming-xu/) ×2 - [Jingwei Cheng](https://md.research.elamur.ai/free/en/authors/jingwei-cheng/) ×2 - [Lu Zhang](https://md.research.elamur.ai/free/en/authors/lu-zhang/) ## 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