Paper Citation Record · LEDGER

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification

As of 18 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2502.02471.

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

pith.paper-citation-record.v1
2502.02471 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T12:03:57.540913Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:51:36.521600Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T23:51:36.586496Z

Reference resolution

30 of 30 outbound references displayed

verified exact0
verified fuzzy19
unresolved11
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4c37f268-5ca4-4352-befe-4d3006d77806 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 1

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Source-reported events for the cited work

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Observation 4f98dca3-e95c-4dbd-b363-7138f14f9fcb · outbound

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

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Towards a general-purpose foundation model for computational pathology

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.818624Z

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Observation d3f48625-c705-431f-abd3-2c13613aa1e3 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Imagenet: A large-scale hierarchical image database

Reference 3

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Observation bd07c135-089f-4976-950f-1706b985793b · outbound

This paper cites PanNuke Dataset Extension, Insights and Baselines.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification PanNuke Dataset Extension, Insights and Baselines

Reference 4

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Observation b476a6d6-8388-4a5e-9ff5-35524e6dc3c7 · outbound

This paper cites Lizard: a large-scale dataset for colonic nuclear instance segmentation and classification.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Lizard: a large-scale dataset for colonic nuclear instance segmentation and classification

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.804641Z

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Observation f2246519-e02d-4ad5-ac31-4119be14d946 · outbound

This paper cites Conic challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Conic challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.795754Z

Source-reported events for the cited work

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Observation cedc4d80-a406-4e79-a9cc-2b538cd7ac60 · outbound

This paper cites Hover-net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Hover-net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.785953Z

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Observation bc78e368-ed3e-44cc-bffa-1b312821dd56 · outbound

This paper cites Cytoarchitectureal changes in hippocampal subregions of the nzb/w f1 mouse model of lupus.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Cytoarchitectureal changes in hippocampal subregions of the nzb/w f1 mouse model of lupus

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.775798Z

Source-reported events for the cited work

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Observation 121205a8-b356-46a0-bf8c-4d9df2a47768 · outbound

This paper cites Age-related changes in the primary auditory cortex of newborn, adults and aging bottlenose dolphins (tursiops truncatus) are located in the upper cortical layers.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Age-related changes in the primary auditory cortex of newborn, adults and aging bottlenose dolphins (tursiops truncatus) are located in the upper cortical layers

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.763725Z

Source-reported events for the cited work

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Observation e495ee62-0a20-4542-857f-e3085203e186 · outbound

This paper cites Unetr: Transformers for 3d medical image segmentation.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Unetr: Transformers for 3d medical image segmentation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.753587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6191aec0-66ab-4418-84ce-abd16445fc6c · outbound

This paper cites Cellvit: Vision transformers for precise cell segmen- tation and classification.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Cellvit: Vision transformers for precise cell segmen- tation and classification

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.744345Z

Source-reported events for the cited work

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Observation 38ec72ae-d6e8-47b4-a91b-7e560ee0fb99 · outbound

This paper cites cellseg models.pytorch: Cell/nuclei segmentation models and benchmark.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification cellseg models.pytorch: Cell/nuclei segmentation models and benchmark

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.734667Z

Source-reported events for the cited work

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Observation 826e5a9d-4b7d-48ac-8820-f199c5ed6a19 · outbound

This paper cites Swin transformer v2: Scaling up capacity and resolution.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Swin transformer v2: Scaling up capacity and resolution

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.725435Z

Source-reported events for the cited work

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Observation 86fa12a3-a5bb-4b9f-8c3c-ed2ac8d624d9 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Swin transformer: Hierarchical vision transformer using shifted windows

Reference 14

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Source-reported events for the cited work

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Observation 2a09dba2-ba90-496c-9b17-40774034d609 · outbound

This paper cites A convnet for the 2020s.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification A convnet for the 2020s

Reference 15

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Source-reported events for the cited work

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Observation 53fceadd-680e-400a-b78a-608b76f1a592 · outbound

This paper cites Fully convo- lutional networks for semantic segmentation.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Fully convo- lutional networks for semantic segmentation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T12:03:57.496633Z

Source-reported events for the cited work

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Observation a1b04500-b936-488d-86ef-6fb1f960fc53 · outbound

This paper cites A visual-language foundation model for computational pathology.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification A visual-language foundation model for computational pathology

Reference 17

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Observation cc749c8d-6373-4315-b2e3-f6324d1b6a06 · outbound

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

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification DINOv2: Learning Robust Visual Features without Supervision

Reference 18

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Source-reported events for the cited work

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Observation 48144023-a389-449a-b842-e4022e44378f · outbound

This paper cites Do vision transformers see like convolutional neural networks? Advances in neural information processing systems, 34:12116–12128, 2021.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Do vision transformers see like convolutional neural networks? Advances in neural information processing systems, 34:12116–12128, 2021

Reference 19

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Source-reported events for the cited work

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Observation d28ffa08-e323-4d57-88f4-7f94f6c1eaa8 · outbound

This paper cites Cell detection with star-convex polygons.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Cell detection with star-convex polygons

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.685624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f66ad115-98fc-4a3e-a48c-ba1ce6eab1ee · outbound

This paper cites Cellpose: a generalist algorithm for cellular segmentation.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Cellpose: a generalist algorithm for cellular segmentation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.675731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 600c1253-4eb2-4d27-98cf-4f75f754fc7b · outbound

This paper cites Maxvit: Multi-axis vision transformer.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Maxvit: Multi-axis vision transformer

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.665485Z

Source-reported events for the cited work

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Observation 8f29f2ea-b232-4d83-b42b-822271a1ce77 · outbound

This paper cites CISCA and CytoDArk0: a Cell Instance Segmentation and Classification method for histo(patho)logical image Analyses and a new, open, Nissl-stained dataset for brain cytoarchitecture studies.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification CISCA and CytoDArk0: a Cell Instance Segmentation and Classification method for histo(patho)logical image Analyses and a new, open, Nissl-stained dataset for brain cytoarchitecture studies

Reference 23

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Source-reported events for the cited work

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Observation 8be9e970-3a71-45f7-a5bc-8d2eeeef6e3a · outbound

This paper cites Cytodark0, September 2024.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Cytodark0, September 2024

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.656476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 993e5261-56d5-4a71-87f4-cade87c8a9a8 · outbound

This paper cites Attention is all you need.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Attention is all you need

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.647265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 235ff926-1794-42ba-977b-1e00c3da6d04 · outbound

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

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification A foundation model for clinical- grade computational pathology and rare cancers detection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.638792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2dfe656d-47d5-467c-adbb-e3a8b67820f8 · outbound

This paper cites A pathology foundation model for cancer diagnosis and prognosis prediction.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification A pathology foundation model for cancer diagnosis and prognosis prediction

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T12:03:57.531716Z

Source-reported events for the cited work

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Observation a3ddf139-317f-4121-b113-4c5bef591bd1 · outbound

This paper cites Pytorch image models.

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Pytorch image models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.624131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cd27ea2f-4860-47ee-8dc9-398b35cc8b84 · outbound

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

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification A whole-slide foundation model for digital pathology from real-world data

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:03:57.613948Z

Source-reported events for the cited work

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Observation 5c9b1882-11fd-4ede-92ec-eaeebe41f305 · outbound

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

Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-09T12:03:57.540913Z

Source-reported events for the cited work

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Pith citing papers

Observation 3f9685e8-b286-4091-beab-288afabb011f · inbound

HistoSmith: Single-Stage Histology Image-Label Generation via Conditional Latent Diffusion for Enhanced Cell Segmentation and Classification cites this paper.

HistoSmith: Single-Stage Histology Image-Label Generation via Conditional Latent Diffusion for Enhanced Cell Segmentation and Classification Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and Classification

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.