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Paper Citation Record · LEDGER

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers

As of 21 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2501.19048.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.19048 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T21:35:33.872507Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

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

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T18:57:21.124816Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T18:57:21.373649Z

Reference resolution

40 of 40 outbound references displayed

  • verified exact24
  • verified fuzzy10
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 008c2c88-6116-4267-9edb-b355375956e5 · outbound

This paper cites Learning whole-slide segmentation from inexact and incomplete labels using tissue graphs.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Learning whole-slide segmentation from inexact and incomplete labels using tissue graphs

Reference 1

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verified exact
doi, observed 2026-08-09T21:35:33.997705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.750501Z digest=sha256:1904d20b84d33eb14ed224f02571f8c881dd3c668ac2450edec8f80d2adba5a4

Observation a9a98888-7ea8-4414-acf4-370295235912 · outbound

This paper cites Van Der Laak, Meyke Hermsen, Quirine F.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Van Der Laak, Meyke Hermsen, Quirine F

Reference 2

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arxiv_id_nonexistent, observed 2026-08-09T21:35:36.626197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.754263Z digest=sha256:962cb4214ad6a0c372af25aa58bd4e20050861ce9e6b31c6836274cab75ba8de

Observation 8c5b127b-74d5-4b81-95d9-e0752d61c392 · outbound

This paper cites Enhancing pfi prediction with gds-mil: A graph-based dual stream mil approach.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Enhancing pfi prediction with gds-mil: A graph-based dual stream mil approach

Reference 3

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raw_fallback, observed 2026-08-09T21:35:36.730930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.757750Z digest=sha256:02f05374a350dbad9004ac9eee2df523a65d5c744d21293c704bb9f508bc1d41

Observation 7affe71f-4a53-45ab-9228-11860d738b85 · outbound

This paper cites Das-mil: Distilling across scales for mil classification of histological wsis.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Das-mil: Distilling across scales for mil classification of histological wsis

Reference 4

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raw_fallback, observed 2026-08-09T21:35:36.721857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.761325Z digest=sha256:68669fe02b18b91221eae86fd7ff66d57ddb3098c09e251bd42b07b3ba8e2acc

Observation 66729253-8d85-4058-8fcc-0c019b83ba36 · outbound

This paper cites Whole slide image quality in digital pathology: Review and perspectives.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Whole slide image quality in digital pathology: Review and perspectives

Reference 5

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arxiv_id_nonexistent, observed 2026-08-09T21:35:36.455542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.764760Z digest=sha256:97ba6af33572dc2aebb5cacf5bde5655925cc01f8c8fb1f00d72b2d00ea82b6f

Observation 061454b2-28a3-4e3c-9c93-6240360d4277 · outbound

This paper cites an unresolved cited work.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Unresolved cited work

Reference 6

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arxiv_id_nonexistent, observed 2026-08-09T21:35:36.181691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.768056Z digest=sha256:f26b926a4bdbbf0cfadd83ef7f3a790acecb3167e7b7659744bd83c6cd1d0612

Observation 817a8784-a6ef-4f91-9931-aa773906b47e · outbound

This paper cites Camil: Causal multiple instance learning for whole slide image classification.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Camil: Causal multiple instance learning for whole slide image classification

Reference 7

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doi, observed 2026-08-09T21:35:33.988238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.771663Z digest=sha256:6b4597ed0f095df4bf492a7a3eecdfc0109f1416581a4f861ed57363614f5a8d

Observation 176b03c9-53c9-4e84-80a6-c2cc14055dd3 · outbound

This paper cites Chen, Ming Y.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Chen, Ming Y

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.774858Z digest=sha256:b9ea7e2cd3afe3c087cd4934bd74ccbe0f4b752b4b02aa21f7e5c6a9999d3af9

Observation 014edc3b-3a12-464b-a158-5bf5c9401433 · outbound

This paper cites Causal inference meets machine learning.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Causal inference meets machine learning

Reference 9

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arxiv_id_nonexistent, observed 2026-08-09T21:35:35.977722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.778051Z digest=sha256:8a355ebce0803a2508d809e2a85a48b1b83a1b06762ec06029806b598be8db92

Observation 2f2fce09-40b0-44ff-b3ad-f41cb0010ad4 · outbound

This paper cites Zuckerman, Tairan Liu, Anthony E.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Zuckerman, Tairan Liu, Anthony E

Reference 10

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doi, observed 2026-08-09T21:35:33.979321Z

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source=arxiv_source observed=2026-08-09T21:35:33.781054Z digest=sha256:0aff1ef9ed2d03e8372e941e6b5449e33c634fb3c0f8b4e86e4f89f39419ff20

Observation a0b190d8-b0aa-487a-9a95-aef0ed748c3b · outbound

This paper cites Combining Graph Neural Network and Mamba to Capture Local and Global Tissue Spatial Relationships in Whole Slide Images.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Combining Graph Neural Network and Mamba to Capture Local and Global Tissue Spatial Relationships in Whole Slide Images

Reference 11

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local_arxiv, observed 2026-08-09T21:35:35.773325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.784369Z digest=sha256:b5d1dc903c16e3d3d936a1b39bc6e09d71001e57e86aa5aa5ea67acb42385432

Observation a75383b7-d106-46e7-8db4-a8759f8ad44d · outbound

This paper cites A comprehensive review on multiple instance learning.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers A comprehensive review on multiple instance learning

Reference 12

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no resolver link, observed 2026-08-09T21:35:33.788284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T21:35:33.788284Z digest=sha256:14f51b3ab4a903e511863d69317a5bb5f5f599ceb67e121cdfecfd11aaad6b3a

Observation 17978fe9-48b2-4334-9e6e-864eedd2e20a · outbound

This paper cites Node-aligned graph convolutional network for whole-slide image representation and classification.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Node-aligned graph convolutional network for whole-slide image representation and classification

Reference 13

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raw_fallback, observed 2026-08-09T21:35:36.704210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.791370Z digest=sha256:2bc437a33bf1fa3b4805ead6a317a609054bd7bf637b49d387376175185e01bd

Observation 78a6e9cf-a7c6-4276-8ee5-e9a44b11724d · outbound

This paper cites Investigating out-of-distribution generalization of gnns: An architecture perspective.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Investigating out-of-distribution generalization of gnns: An architecture perspective

Reference 14

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arxiv_id_nonexistent, observed 2026-08-09T21:35:35.761341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.794377Z digest=sha256:f73b933820a5852a678b948dce551761d362c09b0f917b2cbe4d6d9f2d5c1012

Observation c0dca0a9-413f-4e22-8ea5-d4cd08932f68 · outbound

This paper cites Ziaul Hoque, Anja Keskinarkaus, Pia Nyberg, Taneli Mattila, and Tapio Seppänen.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Ziaul Hoque, Anja Keskinarkaus, Pia Nyberg, Taneli Mattila, and Tapio Seppänen

Reference 15

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arxiv_id_nonexistent, observed 2026-08-09T21:35:35.600612Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.797604Z digest=sha256:9528d20dc9b223ad279f1543ce66ee16dbc19382c04dd22117395ba77270b3b0

Observation 9c522703-4ea1-49da-8214-4c16672f07a4 · outbound

This paper cites Tomczak, and Max Welling.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Tomczak, and Max Welling

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.800556Z digest=sha256:378f403b3562a104413e0d5f6661b530698d01d2e5ce41ce692ba9139bdc6910

Observation 9b525731-7c19-4531-a381-b3a54ea161d9 · outbound

This paper cites an unresolved cited work.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Unresolved cited work

Reference 17

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doi, observed 2026-08-09T21:35:33.965072Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 8e336df2-3987-40b7-a3b2-a31e80a09ae6 · outbound

This paper cites The devil is in the details: Whole slide image acquisition and processing for artifacts detection, color variation, and data augmentation: A review.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers The devil is in the details: Whole slide image acquisition and processing for artifacts detection, color variation, and data augmentation: A review

Reference 18

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arxiv_id_nonexistent, observed 2026-08-09T21:35:35.439588Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation ed9cca2f-b8b7-4238-9c4c-8202c08f2121 · outbound

This paper cites Lubanski, and Peter M.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Lubanski, and Peter M

Reference 19

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doi, observed 2026-08-09T21:35:33.956068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.809681Z digest=sha256:0999a5d2fb0e8ad169c0dc958bed50057ef24efc4c91bd03d9929cd8ac8f5428

Observation c2fe23fb-7874-48b1-aff0-15090380a15c · outbound

This paper cites Kipf and Max Welling.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Kipf and Max Welling

Reference 20

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no resolver link, observed 2026-08-09T21:35:33.812922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T21:35:33.812922Z digest=sha256:83ebf3dc92919decc2b7e40c408c2f029ad795d861e3e72049ac7a844c371378

Observation 29228bce-ec8d-43d9-8fef-2bb846544243 · outbound

This paper cites Machine learning methods for histopathological image analysis.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Machine learning methods for histopathological image analysis

Reference 21

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source=arxiv_source observed=2026-08-09T21:35:33.815977Z digest=sha256:c01518749caab75e46c14345f366df6677a60bc25edd1702e5de4495ead695ce

Observation e80de100-5473-41c2-af77-d2a7586ffe22 · outbound

This paper cites Eliceiri.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Eliceiri

Reference 22

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source=arxiv_source observed=2026-08-09T21:35:33.819079Z digest=sha256:601d1150e6471cfa62a582f8884b656edc5e3a515280db82d7fdf0ae7b3be98d

Observation ba22431a-8658-473a-9999-5ee899e3baca · outbound

This paper cites Graph cnn for survival analysis on whole slide pathological images.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Graph cnn for survival analysis on whole slide pathological images

Reference 23

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raw_fallback, observed 2026-08-09T21:35:36.680662Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.822112Z digest=sha256:1273d4699d787595fb9cd12fc56d30b43b88ba67d474c86d2fb99d0f1aaf7421

Observation bf1e3d8a-e183-49bd-a745-729adbc0d6a0 · outbound

This paper cites A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches

Reference 24

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doi, observed 2026-08-09T21:35:33.936812Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.825069Z digest=sha256:732b3b7b7c641210653bd64e24b939e2864569c4309bedb7ea593fa571277ee9

Observation d0751446-f9f7-4d62-b1f2-d888b6f16642 · outbound

This paper cites Interventional bag multi-instance learning on whole-slide pathological images.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Interventional bag multi-instance learning on whole-slide pathological images

Reference 25

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arxiv_id_nonexistent, observed 2026-08-09T21:35:35.066121Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.828214Z digest=sha256:85f803282f7305b1e3a5e530619c4c1e09234f5eaadf2fe465352e3c7ca90301

Observation a0179304-50d6-4221-9f4f-c74c219c61fe · outbound

This paper cites 1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers 1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset

Reference 26

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no resolver link, observed 2026-08-09T21:35:33.831099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T21:35:33.831099Z digest=sha256:e7c2fad452875fc8c92575fb336e338e052e83d3108182426fd112ac72278278

Observation 1b813d19-839a-4bd4-8c5b-1fc91627851b · outbound

This paper cites Lu, Drew F.K.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Lu, Drew F.K

Reference 27

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no resolver link, observed 2026-08-09T21:35:33.834193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T21:35:33.834193Z digest=sha256:da1cbabe4fb59836b31758805ba3f519b132f0bf132fb7e72edca364f3c4a838

Observation 51aea684-f0af-4168-ae99-4e084191829a · outbound

This paper cites Rita Verdelho, Diogo J.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Rita Verdelho, Diogo J

Reference 28

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raw_fallback, observed 2026-08-09T21:35:36.672177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.837460Z digest=sha256:f8d4ea1741bb25da89fd426064331702bdfb93bd44aafd3c7e43c7de11cccf20

Observation 84281a3c-abcd-40e8-98f6-ba04500ce78e · outbound

This paper cites Graph attention multi-instance learning for accurate colorectal cancer staging.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Graph attention multi-instance learning for accurate colorectal cancer staging

Reference 29

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raw_fallback, observed 2026-08-09T21:35:36.663780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.840363Z digest=sha256:1af7beeeff259ed7a5abc2bb057b5d78ea29c187c09ad7e8e9b602000df46119

Observation d83ddb1f-c4bc-4175-abcd-da1a06458907 · outbound

This paper cites an unresolved cited work.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Unresolved cited work

Reference 30

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arxiv_id_nonexistent, observed 2026-08-09T21:35:34.896402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.843275Z digest=sha256:7d08b100cdf03e759c342db505ab3d1556a7d67585b34b5f3f6f5c5b58b33c41

Observation cb8951e7-d5b4-4846-bace-8b6ab904a4a9 · outbound

This paper cites A structure-aware hierarchical graph-based multiple instance learning framework for pt staging in histopathological image.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers A structure-aware hierarchical graph-based multiple instance learning framework for pt staging in histopathological image

Reference 31

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arxiv_id_nonexistent, observed 2026-08-09T21:35:34.731552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.846119Z digest=sha256:9490a44acd9e0d975d1bcf2bcb493cabe5ba8a933cba6326daea4bcaa5822c65

Observation 4437bdec-d67f-45f8-84f1-5b12b2f29d65 · outbound

This paper cites Attention-based deep multiple instance learning with adaptive instance sampling.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Attention-based deep multiple instance learning with adaptive instance sampling

Reference 32

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arxiv_id_nonexistent, observed 2026-08-09T21:35:34.530086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.848867Z digest=sha256:4cfcae2dc8fd3a4027a945c7c3bdca63d4a400218d5674f906c26921e686c227

Observation 12bf99bd-eec3-4e4b-8a6e-8c76a4f7fffe · outbound

This paper cites an unresolved cited work.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Unresolved cited work

Reference 33

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doi, observed 2026-08-09T21:35:33.918075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.851737Z digest=sha256:00f9ba124eebf2c3290846e7142db4a0899cfc0efecbc72183a5b1ab57af0a72

Observation 22ce0919-fd02-40aa-9c5f-ef77bf3a27c4 · outbound

This paper cites Graph attention networks.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Graph attention networks

Reference 34

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no resolver link, observed 2026-08-09T21:35:33.854537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T21:35:33.854537Z digest=sha256:051a7503442ad15288235b24af1b392d03b48be4c751b1afa4fa42772868d313

Observation 89328947-5fb3-406b-8873-15cded7798e8 · outbound

This paper cites Dual-stream multi-dependency graph neural network enables precise cancer survival analysis.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Dual-stream multi-dependency graph neural network enables precise cancer survival analysis

Reference 35

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T21:35:34.345784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.857430Z digest=sha256:2fc7a45ea11da3f6078becc03c58af39b167b86152720222134573d7bc9fe9f3

Observation 95a90828-b0c0-4887-9a0f-cd00c5c3be2a · outbound

This paper cites Show, attend and tell: Neural image caption generation with visual attention.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Show, attend and tell: Neural image caption generation with visual attention

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T21:35:36.654687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.860508Z digest=sha256:48215bdbb0e7e6f5be613f0ebebb264525f8e60e0b3ba338b7109998dc63f963

Observation 5f871ec1-a64b-4670-b71d-393f41310da4 · outbound

This paper cites Individual and structural graph information bottlenecks for out-of-distribution generalization.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Individual and structural graph information bottlenecks for out-of-distribution generalization

Reference 37

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T21:35:34.166192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.863381Z digest=sha256:ffadfaa33d674d7c4de9ddcd4aad78bf76e70ef489f4401b371dfa6cccc2c8c3

Observation 0377b100-7973-414e-9598-84ab8b72a6f8 · outbound

This paper cites Gigapixel whole-slide images classification using locally supervised learning.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Gigapixel whole-slide images classification using locally supervised learning

Reference 38

Resolution
verified exact
doi, observed 2026-08-09T21:35:33.903001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.866255Z digest=sha256:15b066a71d764e501790014581dd2c9a19a8ab977c95ee0e92e4e4daca24339b

Observation 19b1b2c5-3614-49a0-bce5-045d00b94f8c · outbound

This paper cites Predicting lymph node metastasis using histopathological images based on multiple instance learning with deep graph convolution.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Predicting lymph node metastasis using histopathological images based on multiple instance learning with deep graph convolution

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T21:35:36.645884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.869541Z digest=sha256:6f7238c85ca7452f5df4af5e7d6d982d8cbc1f05c2059c9ce980ec8d556b96be

Observation ce8db77b-63ad-4db1-89ff-1bffa446d896 · outbound

This paper cites an unresolved cited work.

The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-09T21:35:36.635254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-09T21:35:33.872507Z digest=sha256:1e410594c6b348471e28b92f7f84ec45e83a5bef86bbe3ada15ab78bdeef8d72

Pith citing papers

Observation d1dc246d-433e-41a1-b2f9-353d0a41600d · inbound

Integrating Implicit and Explicit Relational Biases through Graph-Based Multiple Instance Learning: A Case Study in Skin Lesion Diagnosis cites this paper.

Integrating Implicit and Explicit Relational Biases through Graph-Based Multiple Instance Learning: A Case Study in Skin Lesion Diagnosis The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers

Reference 17

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T18:57:21.377981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-07T18:57:21.124816Z digest=sha256:41da2829659aaf3c7ce3cd1a6d7054ee51c11df44b6c24767f16f8dd78b263be