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Paper Citation Record · LEDGER

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss

As of 22 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 2 inbound Pith citation observations for arXiv:2507.22092.

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

pith.paper-citation-record.v1
2507.22092 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:29:01.446715Z

measured 28 of 28 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:31:20.364546Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T19:16:30.836659Z

Reference resolution

26 of 26 outbound references displayed

  • verified exact1
  • verified fuzzy15
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 552bfe2e-a9ef-4061-bc89-0069e2b5ebf1 · outbound

This paper cites an unresolved cited work.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss Unresolved cited work

Reference 1

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unresolved
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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.

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Observation 67fea8f2-85e2-4771-a4d0-58860c415410 · outbound

This paper cites H&E-based Computational Biomarker Enables Universal EGFR Screening for Lung Adenocarcinoma.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss H&E-based Computational Biomarker Enables Universal EGFR Screening for Lung Adenocarcinoma

Reference 2

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no resolver link, observed 2026-08-06T12:29:01.375149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 60d51867-0c61-45b0-8906-a890bb3dc0a6 · outbound

This paper cites Nature Medicine30(3), 850–862 (2024).

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss Nature Medicine30(3), 850–862 (2024)

Reference 3

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no resolver link, observed 2026-08-06T12:29:01.378862Z

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Observation aa2e01af-85d8-48c7-90fb-15180a88a48a · outbound

This paper cites https://doi.org/10.7937/K9/TCIA.2018.PAT12TBS.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss https://doi.org/10.7937/K9/TCIA.2018.PAT12TBS

Reference 4

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verified exact
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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.

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Observation 85b08831-6966-4f2b-bc08-a5b2d134e094 · outbound

This paper cites Journal of Pathology Informatics14 (2023).

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss Journal of Pathology Informatics14 (2023)

Reference 5

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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.

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Observation 496b96e0-e9b4-4785-8b60-03baca474927 · outbound

This paper cites medRxiv (2023).

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss medRxiv (2023)

Reference 6

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verified fuzzy
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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.

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Observation c43112c1-958e-4d2a-99c8-0f46ad2a2253 · outbound

This paper cites In: 2006 IEEE computer society conference on computer vision and pattern recognition (CVPR’06).

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss In: 2006 IEEE computer society conference on computer vision and pattern recognition (CVPR’06)

Reference 7

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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.

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Observation c13f7663-9ad8-4f93-911d-6f041d63f355 · outbound

This paper cites In: International conference on machine learning.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss In: International conference on machine learning

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.

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Observation 15d00ca4-79a8-43af-9070-08fc9244b69e · outbound

This paper cites Current Pathology Foundation Models are unrobust to Medical Center Differences.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss Current Pathology Foundation Models are unrobust to Medical Center Differences

Reference 9

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no resolver link, observed 2026-08-06T12:29:01.397272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b53d5ac9-480f-43d2-824d-4a8031f913cc · outbound

This paper cites Frontiers in Medicine8, 746307 (2021).

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss Frontiers in Medicine8, 746307 (2021)

Reference 10

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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.

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Observation 9a98c649-7780-4731-b2a6-950512a3e660 · outbound

This paper cites Nature cancer1(8), 789–799 (2020).

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss Nature cancer1(8), 789–799 (2020)

Reference 11

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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.

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Observation c3111d60-4d3a-489d-a1f6-8961df8032ab · outbound

This paper cites Slot-Mixup with Subsampling: A Simple Regularization for WSI Classification.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss Slot-Mixup with Subsampling: A Simple Regularization for WSI Classification

Reference 12

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no resolver link, observed 2026-08-06T12:29:01.406310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 95f0fcbf-e673-4012-8398-923a49f1e3f8 · outbound

This paper cites In: Pro- ceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni- tion.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss In: Pro- ceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni- tion

Reference 13

Resolution
verified fuzzy
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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.

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Observation 3d683a03-34fc-4b78-a7b8-5fd58712b6cc · outbound

This paper cites In: 2009 IEEE international symposium on biomedical imaging: from nano to macro.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss In: 2009 IEEE international symposium on biomedical imaging: from nano to macro

Reference 14

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unresolved
no resolver link, observed 2026-08-06T12:29:01.412205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:29:01.412205Z digest=sha256:e351b7976ba3b30d29b25d579f975165f387d5c54866ea69e3afd1c483cae332

Observation db99d89b-eb38-435f-9919-129985ebe643 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 15

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unresolved
no resolver link, observed 2026-08-06T12:29:01.415113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 73d660b3-2fc9-4583-8be7-fea509e80500 · outbound

This paper cites Journal of Clinical Oncology40(17), 1916– 1928 (2022) Pathology FMs are Scanner Sensitive: Benchmark & Mitigation 11.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss Journal of Clinical Oncology40(17), 1916– 1928 (2022) Pathology FMs are Scanner Sensitive: Benchmark & Mitigation 11

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.

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Observation 8cc5c33b-a799-4395-a17a-27dcf426d97b · outbound

This paper cites medRxiv (2023).

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss medRxiv (2023)

Reference 17

Resolution
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raw_fallback, observed 2026-08-06T12:29:01.633992Z

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.

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Observation a2e45b80-3083-48da-a4b8-f99eba7c1f77 · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 18

Resolution
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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.

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Observation 2ee54af1-374f-4d39-aa46-1f835118e0a8 · outbound

This paper cites IEEE Computer graphics and applications21(5), 34–41 (2001).

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss IEEE Computer graphics and applications21(5), 34–41 (2001)

Reference 19

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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=pdf_text observed=2026-08-06T12:29:01.426449Z digest=sha256:d7d56c90c7aa2e37a44a1e87e2c9ba274020d708ab6d1515c32de6ae17e2b078

Observation d4064256-0f86-4bd7-bda5-19cf3960b683 · outbound

This paper cites an unresolved cited work.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss Unresolved cited work

Reference 20

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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.

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Observation 8d02c231-3114-440b-9ec5-617c50263ae4 · outbound

This paper cites In: 2019 Ieee 16th international symposium on biomedical imaging (Isbi 2019).

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss In: 2019 Ieee 16th international symposium on biomedical imaging (Isbi 2019)

Reference 21

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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=pdf_text observed=2026-08-06T12:29:01.432322Z digest=sha256:efc18f81cab28eb4f198a3212883f5a3cc58e8dfa826962a532eabf5d0030743

Observation f137faca-2cff-4e46-a85a-ae3d38783bb4 · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 22

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raw_fallback, observed 2026-08-06T12:29:01.580418Z

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.

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Observation 77d4b4ca-3469-48c7-a068-77c916bd241a · outbound

This paper cites Nature pp.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss Nature pp

Reference 23

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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.

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Observation 9eea0da0-db93-440b-b0cb-4f0c91448efb · outbound

This paper cites EXAONEPath 1.0 Patch-level Foundation Model for Pathology.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss EXAONEPath 1.0 Patch-level Foundation Model for Pathology

Reference 24

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 793e7773-2e8d-4b04-875f-395622adfc32 · outbound

This paper cites BMC pulmonary medicine23(1) (2023).

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss BMC pulmonary medicine23(1) (2023)

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-06T12:29:01.559721Z

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.

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Observation 367b53c8-30a9-4953-b523-f80331137300 · outbound

This paper cites Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology.

Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology

Reference 26

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unresolved
no resolver link, observed 2026-08-06T12:29:01.446715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:29:01.446715Z digest=sha256:b79cd09a3b126c023d300f59f7f16f0a287f68b6f2bb9fcfa8919dab28f75367

Pith citing papers

Observation f059d3d0-b778-46f7-ab22-3f5340743f59 · inbound

Enabling clinical use of foundation models for computational pathology cites this paper.

Enabling clinical use of foundation models for computational pathology Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss

Reference 25

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arxiv_id, observed 2026-05-15T19:16:30.841001Z

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.

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Observation c9a5602e-58d0-4b5c-b4fb-b906e5f978c3 · inbound

Robustifying pathology foundation models via fine-tuning cites this paper.

Robustifying pathology foundation models via fine-tuning Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-15T15:31:20.364546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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