Paper Citation Record · LEDGER

A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2501.15724.

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

pith.paper-citation-record.v1
2501.15724 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:21:09.836589Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:08:43.525629Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4db9a669-e0f0-4042-b4ed-a80cc4767d2e · inbound

Beyond the Failures: Rethinking Foundation Models in Pathology cites this paper.

Beyond the Failures: Rethinking Foundation Models in Pathology A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:00:51.033335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9be9ccc0-c1a5-40f8-a1c6-38f4e1baeca8 · inbound

Towards Cellular-Scale Interpretability in Pathology Foundation Models for Biomarker Assessment cites this paper.

Towards Cellular-Scale Interpretability in Pathology Foundation Models for Biomarker Assessment A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T23:34:14.747415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf5d74d4-c015-47c2-8d2f-20cbb524d302 · inbound

PathFLIP: Fine-grained Language-Image Pretraining for Versatile Computational Pathology cites this paper.

PathFLIP: Fine-grained Language-Image Pretraining for Versatile Computational Pathology A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T15:17:38.352516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d18d0360-4157-4af7-a169-2b94eb7420a1 · inbound

Benchmarking Pathology Foundation Models for Breast Cancer Survival Prediction cites this paper.

Benchmarking Pathology Foundation Models for Breast Cancer Survival Prediction A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:46:43.794333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation db0733fe-38cd-4074-a988-241313035d75 · inbound

SlideCheck: Guiding Self-Supervised Pretraining of Pathology Foundation Models via Dataset Distributions cites this paper.

SlideCheck: Guiding Self-Supervised Pretraining of Pathology Foundation Models via Dataset Distributions A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:53:16.209332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a44e45eb-60c9-4ac2-a52e-37b6bbb23d98 · inbound

Democratizing and accelerating AI-driven pathology research through agentic intelligence cites this paper.

Democratizing and accelerating AI-driven pathology research through agentic intelligence A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:08:43.527680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fda15408-954f-4076-9e93-15ac405fe61f · inbound

Harnessing Adversarial Distillation to Customise Debiased, Disease-Specific Pathology Foundation Models for Breast Cancer cites this paper.

Harnessing Adversarial Distillation to Customise Debiased, Disease-Specific Pathology Foundation Models for Breast Cancer A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T00:21:09.836589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.