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most citedTowards a Comprehensive Benchmark for Pathological Lymph Node Metastasis in Breast Cancer Sections

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cs.CV2026

DeCo-MIL: Debiased Counterfactual Reasoning for Long-Tailed Whole Slide Image Analysis

Xiaoxiao Li, Xitong Ling, Jiawen Li +6

Multiple instance learning (MIL) is widely used for weakly supervised whole slide image (WSI) analysis. However, under long-tailed distributions, MIL-based WSI analysis faces a nes…

cs.CV2026

Pretraining Multiple Instance Learning Networks with Multi-Teacher Distillation from Pathology Slide Foundation Models

Mingxi Fu, Jiawen Li, Renao Yan +4

Multiple instance learning (MIL) has become the main paradigm for whole-slide image (WSI) analysis in computational pathology. However, existing MIL aggregators are still typically…

cs.CV2026

ALICE: Learning a General-Purpose Pathology Foundation Model from Vision, Vision-Language, and Slide-Level Experts

Jiawen Li, Tian Guan, Huijuan Shi +5

Foundation models are reshaping computational pathology, yet their capabilities remain shaped by pretraining objectives, data sources, and spatial scales, fragmenting complementary…

cs.CV2026

SlideCheck: Guiding Self-Supervised Pretraining of Pathology Foundation Models via Dataset Distributions

Mingyi He, Xinyi Guo, Xitong Ling +7

Pathology foundation models are pretrained on large streams of WSI-derived patches, while supervision during data construction is often slide-level, sparse, or heterogeneous. This…

cs.CV2026

Is Class Signal Clustered or Routed in Task-Induced Implicit Neural Representation Weight Spaces?

Xinyi Guo, Mingyi He, Haobin Ding +7

Implicit neural representations (INRs) encode images as neural-network weights, making image classification a problem of weight-space classifiability. A natural geometric hypothesi…

cs.CV2026

Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction

Weiming Chen, Xitong Ling, Zhenyang Cai +5

Cell-level dense prediction is central to computational pathology, but remains challenging due to fine-grained histological structures, strong domain shifts, and costly dense annot…

cs.CV2026

A Digital Pathology Resource for Liver Cancer Quantification with Datasets, Benchmarks, and Tools

Ying Xiao, Shimiao Tang, Xitong Ling +11

Liver cancer, especially hepatocellular carcinoma (HCC), imposes a substantial global disease burden. Accurate diagnosis and prognostic assessment directly influence treatment sele…

eess.IV2026

To What Extent Do Token-Level Representations from Pathology Foundation Models Improve Dense Prediction?

Weiming Chen, Xitong Ling, Xidong Wang +10

Pathology foundation models (PFMs) have rapidly advanced and are becoming a common backbone for downstream clinical tasks, offering strong transferability across tissues and instit…