---
title: "Xingyu Zhu · University of Szeged — author profile and papers"
description: "Xingyu Zhu, University of Szeged: 2 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites them in our…"
canonical: "https://research.elamur.ai/free/en/authors/xingyu-zhu/"
---
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# Xingyu Zhu

Xingyu Zhu has 2 papers in our library, in 2026, most of them on [Named entity recognition](https://md.research.elamur.ai/free/en/topics/named-entity-recognition/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Claire Nédellec](https://md.research.elamur.ai/free/en/authors/claire-nedellec/), [Junfeng Fang](https://md.research.elamur.ai/free/en/authors/junfeng-fang/), [Robert Bossy](https://md.research.elamur.ai/free/en/authors/robert-bossy/).

2 papers in our library · 2026

[OpenAlex](https://openalex.org/A5127748408) · [**h-index 0**](https://openalex.org/authors/A5127748408) · [2 works](https://openalex.org/works?filter=author.id:A5127748408) · [0 citations](https://openalex.org/works?filter=author.id:A5127748408&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/xingyu-zhu/#papers) · [⭐ Paper Stars ranking: #14022](https://md.research.elamur.ai/free/en/paper-stars/page/141/#star-14022)

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=Xingyu+Zhu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Xingyu+Zhu) · [dblp](https://dblp.org/search?q=Xingyu+Zhu) · [ACL Anthology](https://aclanthology.org/search/?q=Xingyu+Zhu)

## Affiliations

[🎓**University of Szeged** Szeged · Hungary 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-szeged/)

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 7 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/) · [Biochemistry, Genetics and Molecular Biology · 1 work](https://md.research.elamur.ai/free/en/shelves/biochemistry-genetics-and-molecular-biology/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Molecular Biology · 1 work](https://md.research.elamur.ai/free/en/shelves/biochemistry-genetics-and-molecular-biology/molecular-biology/)

🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Named entity recognition · 1 work](https://md.research.elamur.ai/free/en/topics/named-entity-recognition/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/xingyu-zhu/year/2026/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation](https://md.research.elamur.ai/free/en/papers/zhu-2026-mitigating-hallucinations-large-vision-language/)** *(2026)* Large vision-language models (LVLMs) often describe things that are not in the image. Representation-editing fixes are cheaper than fine-tuning on curated data, but they tend to damage general output quality, causing repetitive or incoherent text. The authors trace this damage to two causes. First, the extracted…
2. **[SCoNE: a Self-Correcting and Noise-Augmented Method for Complex Biological and Chemical Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/zhu-2026-scone-self-correcting-noise-augmented/)** *(2026)* Generative models for biological and chemical NER can handle entities that tagging schemes struggle with, such as nested and discontinuous mentions.

## Co-authors here

6 co-authors with a page, the most papers together first.

- [Claire Nédellec](https://md.research.elamur.ai/free/en/authors/claire-nedellec/)
- [Junfeng Fang](https://md.research.elamur.ai/free/en/authors/junfeng-fang/)
- [Robert Bossy](https://md.research.elamur.ai/free/en/authors/robert-bossy/)
- [Shuo Wang](https://md.research.elamur.ai/free/en/authors/shuo-wang/)
- [Xiangnan He](https://md.research.elamur.ai/free/en/authors/xiangnan-he/)
- [Yonghui Yang](https://md.research.elamur.ai/free/en/authors/yonghui-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/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/)
- [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/): [EACL 2026](https://md.research.elamur.ai/free/en/venues/eacl/2026/)

Updated 2 November 2026
