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Yutong Xie

Yutong Xie has 2 papers in our library, in 2026, most of them on Reasoning, Information retrieval & search; often with Biao Wu, Feilong Tang, Imran Razzak.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 6 · 12 works · 141 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #10789

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

🎓Mohamed bin Zayed University of Artificial IntelligenceAbu Dhabi · United Arab Emirates2025–2026 · 2 paperscurrent🔬Shenzhen Institutes of Advanced TechnologyShenzhen · China2019–2020 · 3 papers🎓Beijing Jiaotong UniversityBeijing · China2025 · 2 papers🎓Sun Yat-sen UniversityGuangzhou · China2019–2020 · 2 papers🏛️Chinese Academy of SciencesBeijing · China2019 · 2 papers🎓University of Chinese Academy of SciencesBeijing · China2019 · 2 papers

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 7The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksMedicine · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksHealth Informatics · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 work

🧭 Topics 2Research subjects and languages the work is about.Information retrieval & search · 1 workReasoning · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. MMCLIP: Cross-Modal Attention Masked Modelling for Medical Language-Image Pre-Training (2026 · 3 citations)
    Medical vision-and-language pretraining usually pairs contrastive learning with masked modelling. Random masking, however, tends to miss small pathological details, and most methods train on either paired image–report data or image-only data, not both. MMCLIP addresses this with two masking modules built on CLIP.…
  2. TAGS: A Test-Time Generalist–Specialist Framework with Retrieval-Augmented Reasoning and Verification (2026 · 1 citation)
    The paper targets a weakness of LLMs in medical question answering. Prompting tricks such as Chain-of-Thought tend to give shallow or unstable reasoning, and fine-tuned medical models struggle when the data distribution shifts. The authors propose TAGS, which runs purely at inference time and changes no model…

 Co-authors here

9 co-authors 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.

Updated

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