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Paper Citation Record · LEDGER

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification

As of 21 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2607.26153.

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pith.paper-citation-record.v1
2607.26153 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T00:40:59.331465Z

measured 27 of 27 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Reference resolution

27 of 27 outbound references displayed

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Outbound references

Observation fe870556-08ef-48b9-bc5e-5b5a799a22f3 · outbound

This paper cites A review of convo- lutional neural network based methods for medical image classifica- tion.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification A review of convo- lutional neural network based methods for medical image classifica- tion

Reference 1

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Observation 25bff549-0fda-4e6c-8cfb-2e4cf027bd80 · outbound

This paper cites Context-Aware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Context-Aware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images

Reference 2

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Observation fdfe533d-f156-497d-827e-0c1746501c4c · outbound

This paper cites Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features

Reference 3

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Observation 5a8968be-200f-405d-820c-73e99e5946bc · outbound

This paper cites Cell-graphs: image-driven modeling of structure- function relationship.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Cell-graphs: image-driven modeling of structure- function relationship

Reference 4

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Observation 62a1bf64-eee7-49bc-acf3-e05201350acb · outbound

This paper cites CGC-Net: Cell Graph Convolutional Network for Grading of Colorectal Cancer Histology Images.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification CGC-Net: Cell Graph Convolutional Network for Grading of Colorectal Cancer Histology Images

Reference 5

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Observation 1c1965a4-f7d9-4adb-b401-9810521f93ce · outbound

This paper cites HAT-Net: A Hierarchical Transformer Graph Neural Network for Grading of Colorectal Cancer Histology Images.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification HAT-Net: A Hierarchical Transformer Graph Neural Network for Grading of Colorectal Cancer Histology Images

Reference 6

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Observation cc44e9bf-fe60-4c6c-b5cc-51ae3bfc5d60 · outbound

This paper cites C2P-GCN: Cell-to-Patch Graph Convolutional Network for Colorectal Cancer Grading.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification C2P-GCN: Cell-to-Patch Graph Convolutional Network for Colorectal Cancer Grading

Reference 7

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Observation 4d54f2e2-d456-4f2b-b08a-8cf35532b519 · outbound

This paper cites Rep- resentation Learning of Histopathology Images using Graph Neural Networks.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Rep- resentation Learning of Histopathology Images using Graph Neural Networks

Reference 8

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Observation 44cb1829-3afc-4120-8fb3-b5db2f6153cf · outbound

This paper cites GraphLSurv: A scalable survival prediction net- work with adaptive and sparse structure learning for histopatholog- ical whole-slide images.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification GraphLSurv: A scalable survival prediction net- work with adaptive and sparse structure learning for histopatholog- ical whole-slide images

Reference 9

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Observation 5bb219ce-e790-4d7e-9a9b-334609559a97 · outbound

This paper cites A Convolutional Neural Network and Graph Convolutional Network Based Framework for Classification of Breast Histopathological Images.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification A Convolutional Neural Network and Graph Convolutional Network Based Framework for Classification of Breast Histopathological Images

Reference 10

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Observation f4ab83dd-63b6-4167-a771-038a59475395 · outbound

This paper cites Fractal graph convolutional network with MLP- mixer based multi-path feature fusion for classification of histopatho- logical images.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Fractal graph convolutional network with MLP- mixer based multi-path feature fusion for classification of histopatho- logical images

Reference 11

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Observation 7288c795-68b9-4a87-9080-e0ca58a2c673 · outbound

This paper cites an unresolved cited work.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Unresolved cited work

Reference 12

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Observation 4fcdba1b-be12-40da-9768-9a8358492f61 · outbound

This paper cites Weakly-supervised deep learn- ing model for prostate cancer diagnosis and gleason grading of histopathology images.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Weakly-supervised deep learn- ing model for prostate cancer diagnosis and gleason grading of histopathology images

Reference 13

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Observation cc63d062-ca8c-4703-a53a-11e70585a2e1 · outbound

This paper cites DARTS: Differentiable Architecture Search.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification DARTS: Differentiable Architecture Search

Reference 14

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Observation d1fb933c-b749-46c2-b9c6-bede498ba0de · outbound

This paper cites Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma

Reference 15

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Observation 776c6a88-67f4-4c18-b101-3c139236dcb9 · outbound

This paper cites HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification

Reference 16

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Observation 7af895d1-58f1-4e77-8975-600a666dcca3 · outbound

This paper cites Dynamic Graph Representation with Knowledge- Aware Attention for Histopathology Whole Slide Image Analysis.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Dynamic Graph Representation with Knowledge- Aware Attention for Histopathology Whole Slide Image Analysis

Reference 17

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Observation 2d50a13f-2fd1-44e9-b014-9d2167cba1b4 · outbound

This paper cites Approximate Bilevel Graph Structure Learning for Histopathology Image Classification.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Approximate Bilevel Graph Structure Learning for Histopathology Image Classification

Reference 18

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Observation 54ad4c73-73e4-413c-9be0-d68bbd3df5da · outbound

This paper cites Cell detection with star-convex polygons.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Cell detection with star-convex polygons

Reference 19

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Observation 821a2296-6cb8-4588-893e-677a4d119af1 · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Categorical Reparameterization with Gumbel-Softmax

Reference 20

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Observation ccc79958-de2a-4a00-8193-e8e39aa0de63 · outbound

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A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Unresolved cited work

Reference 21

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Observation f4731ad1-c0f9-479c-9c86-090d9c7599b5 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 22

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Observation 83309aec-febc-44b5-b78d-b726097b02a3 · outbound

This paper cites Rethinking the Inception Architecture for Computer Vision.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Rethinking the Inception Architecture for Computer Vision

Reference 23

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Observation 84b108de-9e76-49be-9eb3-dc14c729175c · outbound

This paper cites Xception: Deep Learning with Depthwise Separable Convolutions.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Xception: Deep Learning with Depthwise Separable Convolutions

Reference 24

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Observation 7d2bf555-8e58-464c-8c54-f291111e162d · outbound

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A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Unresolved cited work

Reference 25

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Observation fb99d4c2-03f7-4890-afc3-ded5b3ec53bc · outbound

This paper cites Deep Residual Learning for Image Recognition.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification Deep Residual Learning for Image Recognition

Reference 2015

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Observation 83dbc157-b392-48a8-9f8a-f9155adb4d98 · outbound

This paper cites MicroMIL: Graph-Based Multiple Instance Learning for Context-Aware Diagnosis with Microscopic Images.

A Hierarchical Framework for Graph Structure Learning in Histopathology Image Classification MicroMIL: Graph-Based Multiple Instance Learning for Context-Aware Diagnosis with Microscopic Images

Reference 2025

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