collaborators

5 papers

cs.CV2026

PathScale-R1: Cross-scale Reasoning for Pathological Image Analysis

Chi Phan, Tianyi Zhang, Yufeng Wu +7

Pathological diagnosis is inherently multi-scale, requiring the integration of global tissue architecture at low magnification with cellular morphology at higher magnification. How…

cs.CV2026

PathAgentBench: Benchmarking Evidence-Seeking Vision-Language Models on Whole-Slide Pathology Image

Dankai Liao, Tianyi Zhang, Yufeng Wu +6

Whole-slide image (WSI) diagnosis requires identifying diagnostically relevant regions, examining them across magnifications, and integrating multi-scale evidence. However, most ex…

cs.CV2026

Enhancing Pathological VLMs with Cross-scale Reasoning

Chi Phan, Tianyi Zhang, Qiaochu Xue +5

Pathological images are inherently multi-scale, requiring pathologists to integrate evidence from global tissue architecture at low magnification to cellular morphology at higher m…

cs.CV2026

Geometry-Aware State Space Model: A New Paradigm for Whole-Slide Image Representation

Enhui Chai, Sicheng Chen, Tianyi Zhang +4

Accurate analysis of histopathological images is critical for disease diagnosis and treatment planning. Whole-slide images (WSIs), which digitize tissue specimens at gigapixel reso…

eess.IV2026

PathRWKV: Enhancing Whole Slide Image Inference with Asymmetric Recurrent Modeling

Tianyi Zhang, Sicheng Chen, Borui Kang +6

Whole Slide Imaging (WSI) has become a gold standard in cancer diagnosis, inspecting multi-scale information from cellular to tissue levels. Processing an entire WSI directly is in…