Paper Citation Record · LEDGER

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models

As of 23 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2607.20584.

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

pith.paper-citation-record.v1
2607.20584 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T10:56:35.849148Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

23 of 23 outbound references displayed

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External citation measurements

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Outbound references

Observation 621c4eea-ca35-4a1e-9bdb-89df6103cd9c · outbound

This paper cites GANs trained by a two time- scale update rule converge to a local Nash equilibrium.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models GANs trained by a two time- scale update rule converge to a local Nash equilibrium

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.774317Z

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Observation d65333a5-5f9f-4b80-aa5e-36d032958730 · outbound

This paper cites The Fréchet distance between multivariate normal distributions.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models The Fréchet distance between multivariate normal distributions

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.778471Z

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Observation 4384a21c-eed2-4b18-96c8-1a225b55c1cc · outbound

This paper cites Rethinking the Inception architecture for computer vision.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Rethinking the Inception architecture for computer vision

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.781838Z

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Observation 186bb01f-c157-4f7b-a1ee-66a40c46a051 · outbound

This paper cites Effectively Unbiased FID and Inception Score and where to find them.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Effectively Unbiased FID and Inception Score and where to find them

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.785408Z

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Observation dd3e5c5d-d879-44af-a3f5-d29ea72053e2 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models DINOv2: Learning Robust Visual Features without Supervision

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.789808Z

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Observation 82291491-5551-4708-94a6-278cb47b9cbe · outbound

This paper cites Towards a general-purpose foundation model for computa- tional pathology.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Towards a general-purpose foundation model for computa- tional pathology

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.793478Z

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Observation e6e6b8af-b69d-47c4-98dd-76ddcdc6b63f · outbound

This paper cites A foundation model for clinical-grade computational pathology and rare cancers detection.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models A foundation model for clinical-grade computational pathology and rare cancers detection

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.796753Z

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Observation 536117bb-de83-43d8-9cdf-d13baf09777a · outbound

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

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.799703Z

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Observation 95fe1282-91b7-4695-a3b0-394661ae1f58 · outbound

This paper cites Scaling self-supervised learning for histopathology with masked image modeling.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Scaling self-supervised learning for histopathology with masked image modeling

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.803064Z

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Observation c86af173-2195-469c-ab7b-57080176b113 · outbound

This paper cites Phikon-v2, A large and public feature extractor for biomarker prediction.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Phikon-v2, A large and public feature extractor for biomarker prediction

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.807057Z

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Observation b99e66ae-4923-4b30-83a8-c33c501c48f2 · outbound

This paper cites Nature Medicine, 2024;30:863–874.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Nature Medicine, 2024;30:863–874

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.810593Z

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Observation e2fa5a74-10d9-447d-9ab4-a3d9bf38f823 · outbound

This paper cites A whole-slide foundation model for digital pathology from real-world data.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models A whole-slide foundation model for digital pathology from real-world data

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.814108Z

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Observation 0303ff15-ad53-4c99-bd2b-355abf9d880a · outbound

This paper cites Improved Precision and Recall Metric for Assessing Generative Models.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Improved Precision and Recall Metric for Assessing Generative Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.817343Z

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Observation 298e65b2-000e-41c7-b8b3-79b95ae4a079 · outbound

This paper cites Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.821032Z

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Observation d2af9f15-f45d-4a85-bc42-be5600ea024e · outbound

This paper cites Toward a shared vision for cancer genomic data (NCI Genomic Data Commons).

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Toward a shared vision for cancer genomic data (NCI Genomic Data Commons)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.824404Z

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Observation ff50daa9-03c3-4036-ab1c-a9d95eb07433 · outbound

This paper cites PixCell: a generative foundation model for digital histopathology images.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models PixCell: a generative foundation model for digital histopathology images

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.827436Z

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Observation 66cdf29a-1ba9-4865-828f-2cdd887890bf · outbound

This paper cites SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.830674Z

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Observation 9fe12178-1710-48ed-8e8f-758090ccf915 · outbound

This paper cites REPA-E: unlocking VAE for end-to-end tuning with latent diffusion transformers.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models REPA-E: unlocking VAE for end-to-end tuning with latent diffusion transformers

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.833787Z

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Observation 7b399119-ee0c-4ce7-8021-4e8c7ae8d3f4 · outbound

This paper cites A method for normalizing histology slides for quantitative analysis.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models A method for normalizing histology slides for quantitative analysis

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.836843Z

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Observation 9e75cc5f-158b-45d0-8375-7a4861974052 · outbound

This paper cites an unresolved cited work.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Unresolved cited work

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.839727Z

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Observation 344b79ec-16a4-4357-af6d-9939eb70d454 · outbound

This paper cites Structure-preserving color normalization and sparse stain separation for histological images.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Structure-preserving color normalization and sparse stain separation for histological images

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.842824Z

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Observation ceceff36-4e87-4cbc-952c-87a89c925b1f · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models Image quality assessment: from error visibility to structural similarity

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.845996Z

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Observation 0825bc78-6150-4443-8680-05d581fde491 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models The unreasonable effectiveness of deep features as a perceptual metric

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.849148Z

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Pith citing papers

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