Paper Citation Record · LEDGER

Comparative Analysis of Diffusion Generative Models in Computational Pathology

As of 15 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2411.15719.

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

pith.paper-citation-record.v1
2411.15719 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:02:42.442917Z

measured 42 of 42 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:02:35.047480Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T21:02:35.573670Z

Reference resolution

41 of 41 outbound references displayed

verified exact1
verified fuzzy28
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6fa3a13c-7931-4dc6-83bc-14182c8a5a4d · outbound

This paper cites Digital pathology: advantages, limitations and emerging perspectives.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Digital pathology: advantages, limitations and emerging perspectives

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.784880Z

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 c1cde2b7-c632-42b1-a7b0-b1a9fadf524a · outbound

This paper cites Dig- ital pathology and artificial intelligence in translational medicine and clinical practice.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Dig- ital pathology and artificial intelligence in translational medicine and clinical practice

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.776175Z

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 2cd70147-b99b-42d8-89b1-d51b458467ca · outbound

This paper cites Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.767686Z

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 98a2c3aa-8364-4876-8374-40474f381364 · outbound

This paper cites Deep learning in histopathology: the path to the clinic.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Deep learning in histopathology: the path to the clinic

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.759709Z

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 8ee7e2b3-89a6-4e9c-8eb5-a9438dff4e98 · outbound

This paper cites Deep learning in cancer pathology: a new generation of clinical biomarkers.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Deep learning in cancer pathology: a new generation of clinical biomarkers

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.751724Z

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 ace79fe6-ef6c-44e7-aea1-483b5ddc0049 · outbound

This paper cites How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?.

Comparative Analysis of Diffusion Generative Models in Computational Pathology How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.346866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa358aa5-0557-4e57-97c8-642fb1931ee5 · outbound

This paper cites Privacy in the age of medical big data.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Privacy in the age of medical big data

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.743479Z

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 9a06d4d1-50ff-4001-ac81-0361d067d152 · outbound

This paper cites Between generating noise and generating images: Noise in the correct frequency improves the quality of synthetic histopathology images for digital pathology.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Between generating noise and generating images: Noise in the correct frequency improves the quality of synthetic histopathology images for digital pathology

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.735769Z

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 3cbf81d1-7fe6-4d3b-adb6-e98a1874078f · outbound

This paper cites Computational pathology: a sur- vey review and the way forward.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Computational pathology: a sur- vey review and the way forward

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.727883Z

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 327fc63e-35e9-48e2-b0e6-311124751a47 · outbound

This paper cites Evaluation of the use of single-and multi- magnification convolutional neural networks for the determination and quantitation of lesions in nonclinical pathology studies.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Evaluation of the use of single-and multi- magnification convolutional neural networks for the determination and quantitation of lesions in nonclinical pathology studies

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.719319Z

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 0ecb47c5-e162-4819-9a53-d9504f2ac033 · outbound

This paper cites Synthetic data in machine learning for medicine and healthcare.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Synthetic data in machine learning for medicine and healthcare

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.710388Z

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 cabc9173-8f22-400b-884b-80cad3cb8a36 · outbound

This paper cites Gen- erative adversarial networks.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Gen- erative adversarial networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.701102Z

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 f41d1b45-b409-4742-a7c8-3a589fefe6f8 · outbound

This paper cites A disentangled generative model for disease decomposition in chest x-rays via normal image synthesis.

Comparative Analysis of Diffusion Generative Models in Computational Pathology A disentangled generative model for disease decomposition in chest x-rays via normal image synthesis

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.692635Z

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 f0bf1008-894f-4406-a2a9-c854b64ee9e7 · outbound

This paper cites Hi- net: hybrid-fusion network for multi-modal mr image synthesis.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Hi- net: hybrid-fusion network for multi-modal mr image synthesis

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.683464Z

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 e04cb939-5de3-49b9-8202-68756e06414b · outbound

This paper cites PathologyGAN: Learning deep representations of cancer tissue.

Comparative Analysis of Diffusion Generative Models in Computational Pathology PathologyGAN: Learning deep representations of cancer tissue

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-12T14:02:42.502026Z

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 e544eb3a-b8bd-4e42-8e6d-498cdd2176ef · outbound

This paper cites Deep semi supervised generative learning for automated tumor proportion scoring on nsclc tissue needle biopsies.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Deep semi supervised generative learning for automated tumor proportion scoring on nsclc tissue needle biopsies

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.674135Z

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 a3e8e0df-7c9f-4682-8cb9-429f021446d0 · outbound

This paper cites Deepfake histologic images for enhancing digital pathology.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Deepfake histologic images for enhancing digital pathology

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.663727Z

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 126248a9-b98d-40cc-a638-a91c895fae76 · outbound

This paper cites Denoising diffusion prob- abilistic models.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Denoising diffusion prob- abilistic models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.380271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d22dcce-664e-4cb6-8f2d-1b5613e387bc · outbound

This paper cites Generative modeling by estimating gradients of the data distribution.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Generative modeling by estimating gradients of the data distribution

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.650506Z

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 4d7d1ad2-94d9-4f7e-bd18-c72fe0bad526 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Score-Based Generative Modeling through Stochastic Differential Equations

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.385671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a021a709-2b1e-4dee-a76b-ae7e34cbeea0 · outbound

This paper cites Diffusion models beat gans on image synthesis.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Diffusion models beat gans on image synthesis

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.641910Z

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 96d3af8a-0422-48b1-950e-5e407a45720f · outbound

This paper cites Improved denoising diffusion probabilistic models.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Improved denoising diffusion probabilistic models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.391614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5881b894-b401-4142-ab4d-ed8fdf709387 · outbound

This paper cites Improved techniques for training score- based generative models.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Improved techniques for training score- based generative models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.629361Z

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 f314fe96-e16a-4064-be9b-336d8cf66a49 · outbound

This paper cites Srdiff: Single image super-resolution with diffusion probabilistic models.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Srdiff: Single image super-resolution with diffusion probabilistic models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.397378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f641010f-5100-4cc4-9dd0-5d9f13e82aca · outbound

This paper cites Diffmix: Diffusion model-based data synthesis for nuclei segmentation and classification in imbalanced pathology image datasets.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Diffmix: Diffusion model-based data synthesis for nuclei segmentation and classification in imbalanced pathology image datasets

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.616721Z

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 742f6574-8b4c-482b-8de5-baa80e24b075 · outbound

This paper cites Card: Classifica- tion and regression diffusion models.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Card: Classifica- tion and regression diffusion models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.608309Z

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 b6a7dd0c-4e29-4e53-8f0c-84e4869dfe5b · outbound

This paper cites Pathldm: Text conditioned la- tent diffusion model for histopathology.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Pathldm: Text conditioned la- tent diffusion model for histopathology

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.599465Z

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 83648b53-bb89-4edb-b278-207beb4a7098 · outbound

This paper cites A morphology focused diffusion probabilistic model for synthesis of histopathology images.

Comparative Analysis of Diffusion Generative Models in Computational Pathology A morphology focused diffusion probabilistic model for synthesis of histopathology images

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.589508Z

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 e63e484d-48fe-4361-905b-3535866e2e08 · outbound

This paper cites Learned representation-guided diffusion models for large-image generation.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Learned representation-guided diffusion models for large-image generation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.581143Z

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 633634b2-2da6-445e-a9bb-09fecac66774 · outbound

This paper cites A boosted classifier for integrating multiple fields of view: Breast can- cer grading in histopathology.

Comparative Analysis of Diffusion Generative Models in Computational Pathology A boosted classifier for integrating multiple fields of view: Breast can- cer grading in histopathology

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.572442Z

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 827e46d5-d325-4d26-979f-1e0ae26f0a9f · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermody- namics.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Deep unsupervised learning using nonequilibrium thermody- namics

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.563159Z

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 10abff81-f5f9-4448-92b5-e77c8e9e688b · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Comparative Analysis of Diffusion Generative Models in Computational Pathology High-resolution image synthesis with latent diffusion models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.419991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5038cde5-72b1-46f8-b217-23a7b7730199 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Classifier-Free Diffusion Guidance

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.422615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2f35f99-01f7-480e-bce6-f1b4c5a4c621 · outbound

This paper cites Elucidating the Exposure Bias in Diffusion Models.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Elucidating the Exposure Bias in Diffusion Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.425834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81639c76-4062-482c-a669-db73665ad545 · outbound

This paper cites Neural discrete representation learning.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Neural discrete representation learning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.428692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dcc3961-ac7b-48de-910d-1d5f2a5f90a9 · outbound

This paper cites Improved techniques for training gans.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Improved techniques for training gans

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.431233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8324fa6-0d5e-460a-bdb9-804ebd07a836 · outbound

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

Comparative Analysis of Diffusion Generative Models in Computational Pathology Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.539802Z

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 30970365-a1ac-4b15-8e3e-0f66fae67fdc · outbound

This paper cites Going deeper with convolutions.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Going deeper with convolutions

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.531427Z

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 0904cc20-2797-49dd-8e84-52eb8341a08b · outbound

This paper cites Demystifying MMD GANs.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Demystifying MMD GANs

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.438227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 663e8af9-d39d-48b4-b2a7-76a0e39d01c0 · outbound

This paper cites Deep resid- ual learning for image recognition.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Deep resid- ual learning for image recognition

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T14:02:42.440664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84568d01-0987-49dd-8fad-56d4310a9971 · outbound

This paper cites Generating synthetic data in digital pathology through diffusion models: a multi- faceted approach to evaluation.

Comparative Analysis of Diffusion Generative Models in Computational Pathology Generating synthetic data in digital pathology through diffusion models: a multi- faceted approach to evaluation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:02:42.518853Z

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.

Pith citing papers

Observation 58cb1a53-5a4b-4e27-b631-6e9fed51dc99 · inbound

Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges cites this paper.

Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges Comparative Analysis of Diffusion Generative Models in Computational Pathology

Reference 114

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:02:35.577273Z

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.