Paper Citation Record · LEDGER

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning

As of 15 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 2 inbound Pith citation observations for arXiv:2411.13623.

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

pith.paper-citation-record.v1
2411.13623 v3

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:40:23.088650Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:17:37.841450Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T21:17:38.017172Z

Reference resolution

47 of 47 outbound references displayed

verified exact0
verified fuzzy37
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c0709f51-739c-46aa-a0a5-fc0154683bb4 · outbound

This paper cites an unresolved cited work.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Unresolved cited work

Reference 1

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Source-reported events for the cited work

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Observation 697c5952-3479-4704-a7d9-a3b7ee9f93b5 · outbound

This paper cites The cbio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning The cbio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.823618Z

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Observation c679c1a3-c837-4352-8981-73ea1de0e2ab · outbound

This paper cites Chen, Chengkuan Chen, Yicong Li, Tiffany Y.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Chen, Chengkuan Chen, Yicong Li, Tiffany Y

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.804536Z

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Observation 87a8ecd0-519d-4c45-bb0b-91ddfcb58ed3 · outbound

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

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Towards a general-purpose foundation model for com- putational pathology

Reference 4

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Observation 281a7e82-1d60-402a-a395-3d4ac062565e · outbound

This paper cites An Empirical Study of Training Self-Supervised Vision Transformers.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning An Empirical Study of Training Self-Supervised Vision Transformers

Reference 5

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Observation 84d1323b-cffd-4b7c-8fd6-8c6c5373f766 · outbound

This paper cites Transformers are ssms: General- ized models and efficient algorithms through structured state space duality, 2024.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Transformers are ssms: General- ized models and efficient algorithms through structured state space duality, 2024

Reference 6

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Observation 0a9d86e5-e35b-47e7-9482-605ec6104aa7 · outbound

This paper cites Dietterich, Richard H.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Dietterich, Richard H

Reference 7

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Observation c66b1f20-83c7-4a2c-b33b-c281077c3b5e · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning An image is worth 16x16 words: Transformers for image recognition at scale

Reference 8

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Observation 8976d070-bfe3-467d-90af-6155b151ba2c · outbound

This paper cites The cptac data portal: A resource for cancer proteomics research.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning The cptac data portal: A resource for cancer proteomics research

Reference 9

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Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Unresolved cited work

Reference 10

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Observation b0b3a95f-6536-46f0-b58d-e757f8b996d7 · outbound

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

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Scaling self-supervised learning for histopathology with masked image modeling

Reference 11

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Observation 3d3aa8b3-d656-47bd-81d6-30fd9f9dc748 · outbound

This paper cites Mamba: Linear-time sequence mod- eling with selective state spaces, 2024.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Mamba: Linear-time sequence mod- eling with selective state spaces, 2024

Reference 12

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Observation 50bb656c-859d-4da6-bfb1-d02c8c1ed932 · outbound

This paper cites Momentum contrast for unsupervised visual repre- sentation learning.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Momentum contrast for unsupervised visual repre- sentation learning

Reference 13

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Observation 8e7630c2-502f-4f1c-a627-6d68fd26b433 · outbound

This paper cites Gaussian error linear units (gelus), 2023.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Gaussian error linear units (gelus), 2023

Reference 14

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Observation 48febb8e-2e8b-40e1-b2f5-6782fe1927d6 · outbound

This paper cites Huang, F.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Huang, F

Reference 15

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Observation 43e7bca0-0300-4fa1-b9ae-4a269e6e19f6 · outbound

This paper cites Attention-based deep multiple instance learning.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Attention-based deep multiple instance learning

Reference 16

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Observation 71cfb981-05a3-4563-9eed-7b27dc07180d · outbound

This paper cites Chen, Drew F.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Chen, Drew F

Reference 17

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Observation fd2cf2c9-184e-435e-9f43-54d52f2cfa89 · outbound

This paper cites Chen, Sharifa Sahai, Dandan Mo, Emilio Madrigal, Long Phi Le, and Mahmood Faisal.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Chen, Sharifa Sahai, Dandan Mo, Emilio Madrigal, Long Phi Le, and Mahmood Faisal

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.612590Z

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Observation 7c725db2-74b3-4273-89c3-2b8f5cfa4bd9 · outbound

This paper cites Benchmarking self-supervised learning on diverse pathology datasets.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Benchmarking self-supervised learning on diverse pathology datasets

Reference 19

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Observation e9a09b20-eaf0-496a-82c6-22e7b6a4f8c6 · outbound

This paper cites Self-path: Self-supervision for classification of pathology images with limited annotations, 2020.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Self-path: Self-supervision for classification of pathology images with limited annotations, 2020

Reference 20

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Observation 845e2a1b-1ae8-44a8-88de-28a29d33121b · outbound

This paper cites Giga-ssl: Self-supervised learning for gi- gapixel images.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Giga-ssl: Self-supervised learning for gi- gapixel images

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.571929Z

Source-reported events for the cited work

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Observation 4f23050b-7d81-49b0-87c8-b0907fb24d6f · outbound

This paper cites Decoupled weight decay regularization, 2019.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Decoupled weight decay regularization, 2019

Reference 22

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Observation dbe0e01b-a6e4-4210-bf33-437dbd6380a7 · outbound

This paper cites Data-efficient and weakly supervised computational pathology on whole- slide images.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Data-efficient and weakly supervised computational pathology on whole- slide images

Reference 23

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Observation 8c8ed321-5108-4805-ba23-604d2b589e17 · outbound

This paper cites Williamson, et al.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Williamson, et al

Reference 24

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Observation b331503b-b149-4e66-89a1-720e36b6652d · outbound

This paper cites Umap: Uniform manifold approximation and projection.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Umap: Uniform manifold approximation and projection

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.513980Z

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Observation a7549b29-9390-4434-bc11-0262d4fb51c7 · outbound

This paper cites Sheridan, Ali Foroughi pour, and Jeffrey H.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Sheridan, Ali Foroughi pour, and Jeffrey H

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.499340Z

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Observation f535dec9-2991-43fb-b465-809693851765 · outbound

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Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Unresolved cited work

Reference 27

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Observation 772f259b-077d-4a7d-950c-4cbe352eddc4 · outbound

This paper cites Hibou: A family of foundational vision transformers for pathology, 2024.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Hibou: A family of foundational vision transformers for pathology, 2024

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.469726Z

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Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Unresolved cited work

Reference 29

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Observation dd7d4b67-97d4-49f2-888c-970343ff21e4 · outbound

This paper cites Dinov2: Learning robust visual features with- out supervision, 2024.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Dinov2: Learning robust visual features with- out supervision, 2024

Reference 30

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Observation 107fef38-3e77-4fdc-ad5d-44905d7facbb · outbound

This paper cites An improved canny edge detection algorithm.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning An improved canny edge detection algorithm

Reference 31

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Observation 347bb5b2-3405-4a7c-952b-1961c37964f5 · outbound

This paper cites H-optimus-0, 2024.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning H-optimus-0, 2024

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.410030Z

Source-reported events for the cited work

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Observation 24c11751-9611-4909-9b32-5df6d88b2d96 · outbound

This paper cites Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Ba- tra.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Ba- tra

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.395062Z

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Observation 63d92917-1b3d-4f4e-bff2-7f79ac7079b7 · outbound

This paper cites Kunz, Juan A.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Kunz, Juan A

Reference 34

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Observation afec7f9d-74d1-4223-9bef-80960760fa69 · outbound

This paper cites Transmil: Transformer based correlated multiple instance learning for whole slide image classification.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Transmil: Transformer based correlated multiple instance learning for whole slide image classification

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.359566Z

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Observation 13cb3a0d-7bac-4384-8378-dadaa66b03c8 · outbound

This paper cites The cancer genome atlas pan-cancer analysis project.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning The cancer genome atlas pan-cancer analysis project

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.342491Z

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Observation 378d2c0f-6c9a-4b33-b1af-851d4bdc2b38 · outbound

This paper cites A systematic analysis of deep learning in genomics and histopathology for precision oncology.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning A systematic analysis of deep learning in genomics and histopathology for precision oncology

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.327799Z

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Observation a8033b80-dac0-4390-8eff-92dcb160f6f8 · outbound

This paper cites Repre- sentation learning with contrastive predictive coding, 2019.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Repre- sentation learning with contrastive predictive coding, 2019

Reference 38

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Observation e0c4ad86-0f7b-4b9f-b9d6-75e1915f28d7 · outbound

This paper cites V orontsov, A.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning V orontsov, A

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.300528Z

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Observation b8d7117a-a6bd-4aa0-b5c0-63129bb2b4c1 · outbound

This paper cites Transformer-based biomarker predic- tion from colorectal cancer histology: A large-scale multi- centric study.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Transformer-based biomarker predic- tion from colorectal cancer histology: A large-scale multi- centric study

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.284601Z

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Observation 13bb72a2-911c-45e1-a864-f68969d98eb7 · outbound

This paper cites Transformer-based unsupervised contrastive learning for histopathological image classification.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Transformer-based unsupervised contrastive learning for histopathological image classification

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.255761Z

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Observation 68458097-98ed-44ce-a03c-2b918744e43c · outbound

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Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Unresolved cited work

Reference 42

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Observation 3bdf586b-d2e3-406a-9007-4f9abcf93ee6 · outbound

This paper cites Meneghetti, Omar S.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Meneghetti, Omar S

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.222552Z

Source-reported events for the cited work

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Observation e295b9db-7953-4a55-991d-2ec012f5005b · outbound

This paper cites Wright, Ari Robicsek, Brian Piening, Carlo Bifulco, Sheng Wang, and Hoifung Poon.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Wright, Ari Robicsek, Brian Piening, Carlo Bifulco, Sheng Wang, and Hoifung Poon

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.205435Z

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Observation e88dd3a2-d638-43c1-a259-64b1c9701026 · outbound

This paper cites MambaMIL: En- hancing Long Sequence Modeling with Sequence Reorder- ing in Computational Pathology.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning MambaMIL: En- hancing Long Sequence Modeling with Sequence Reorder- ing in Computational Pathology

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.190065Z

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Observation 9850c924-6b31-4e4f-96aa-26e4b58fda23 · outbound

This paper cites Slpd: Slide-level prototypical distillation for wsis, 2023.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Slpd: Slide-level prototypical distillation for wsis, 2023

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:40:23.173680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a9e80af9-ca0f-4d10-bb45-741a85076702 · outbound

This paper cites Virchow2: Scaling self-supervised mixed magnification models in pathology, 2024.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning Virchow2: Scaling self-supervised mixed magnification models in pathology, 2024

Reference 47

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T16:40:23.156042Z

Source-reported events for the cited work

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Pith citing papers

Observation 7d42cdbf-da51-4184-83dc-03dda0d29d65 · inbound

Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charit\'e, and Aignostics cites this paper.

Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charit\'e, and Aignostics Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:17:38.021904Z

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Observation c10c1b6b-1c7e-486b-b617-07824e5ebd86 · inbound

Atlas 2 -- Foundation models for clinical deployment cites this paper.

Atlas 2 -- Foundation models for clinical deployment Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T11:50:33.488693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.