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Shaolin Zhu

Shaolin Zhu has 2 papers in our library, in 2023–2026, most of them on Machine translation; often with Deyi Xiong.

2 papers in our library · 2023–2026

OpenAlex · ORCID · h-index 9 · 39 works · 225 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 19 times in our library · ⭐ Paper Stars ranking: #8400

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Tianjin UniversityTianjin · China2023–2026 · 21 paperscurrent🎓Zhengzhou University of Light IndustryZhengzhou · China2020–2024 · 8 papers🏛️Chinese Academy of SciencesBeijing · China2017–2019 · 4 papers🔬Xinjiang Technical Institute of Physics & ChemistryÜrümqi · China2017–2019 · 4 papers🎓University of Chinese Academy of SciencesBeijing · China2017–2019 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 1Research subjects and languages the work is about.Machine translation · 1 work

 Works by year

2020s

20261 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. PEIT: Bridging the Modality Gap with Pre-trained Models for End-to-End Image Translation (2023 · 32 citations)
    Image translation (IT) converts text embedded in an image from one language into another. Cascaded OCR+MT pipelines accumulate errors and are slow. End-to-end models struggle because visual text and textual MT inputs are represented very differently. The authors propose PEIT, which uses pre-trained components to…
  2. AdaDPI: Document-level Translation Adaptive Agent via Dynamic Parametric Internalization (2026)
    Document-level machine translation (DocMT) with LLMs often loses track of terminology, pronoun referents and style across long texts.

 Co-authors here

1 co-author with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 19 times (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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