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Yuxuan Sun

4 papers hereh-index 8474 citations27 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • eess.IV1
same name
  • Yuxuan Sun — 9 papers, h 5
  • Yuxuan Sun — 4 papers, h 3
  • Yuxuan Sun — 4 papers, h 9
  • Yuxuan Sun — 4 papers, h 19
  • Yuxuan Sun — 3 papers, h 1
  • Yuxuan Sun — 3 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators

4 papers

cs.CV2026

NuNext: Reframing Nucleus Detection as Next-Point Detection

Zhongyi Shui, Honglin Li, Xiaozhong Ji +7

Nucleus detection in histopathology is pivotal for a wide range of clinical applications. Existing approaches either regress nuclear proxy maps that require complex post-processing…

eess.IV2026

Towards Effective and Efficient Context-aware Nucleus Detection in Histopathology Whole Slide Images

Zhongyi Shui, Honglin Li, Yunlong Zhang +7

Nucleus detection in histopathology whole slide images (WSIs) is crucial for a broad spectrum of clinical applications. The gigapixel size of WSIs necessitates the use of sliding w…

cs.CV2025

CPathAgent: An Agent-based Foundation Model for Interpretable High-Resolution Pathology Image Analysis Mimicking Pathologists' Diagnostic Logic

Yuxuan Sun, Yixuan Si, Chenglu Zhu +5

Recent advances in computational pathology have led to the emergence of numerous foundation models. These models typically rely on general-purpose encoders with multi-instance lear…

cs.CV2024

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology

Yuxuan Sun, Yixuan Si, Chenglu Zhu +7

The emergence of large multimodal models (LMMs) has brought significant advancements to pathology. Previous research has primarily focused on separately training patch-level and wh…

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