Paper Citation Record · LEDGER

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics

As of 15 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2507.05063.

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

pith.paper-citation-record.v1
2507.05063 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:36:46.883754Z

measured 23 of 23 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 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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verified fuzzy16
unresolved5
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fcaa7a16-8abd-406e-89c7-b83a7ca6068c · outbound

This paper cites Machine learning in rare disease.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Machine learning in rare disease

Reference 1

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Source-reported events for the cited work

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Observation e80bf4f9-90e9-423b-bf04-375e4d32a579 · outbound

This paper cites Improving image generation with better captions.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Improving image generation with better captions

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.393518Z

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Observation 3d836a33-7b37-41c2-8334-1dc2c83ebe93 · outbound

This paper cites PathDiff: Histopathology Image Synthesis with Unpaired Text and Mask Conditions.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics PathDiff: Histopathology Image Synthesis with Unpaired Text and Mask Conditions

Reference 3

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Observation 117921f4-6ae8-4b45-8167-f594bf2c789f · outbound

This paper cites Simple Drop-in LoRA Conditioning on Attention Layers Will Improve Your Diffusion Model.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Simple Drop-in LoRA Conditioning on Attention Layers Will Improve Your Diffusion Model

Reference 4

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Observation c60ac079-0315-40dd-bd5b-d8f85201bf5b · outbound

This paper cites Synthetic medical images for robust, privacy-preserving training of ar- tificial intelligence: application to retinopathy of prematurity diagnosis.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Synthetic medical images for robust, privacy-preserving training of ar- tificial intelligence: application to retinopathy of prematurity diagnosis

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.375054Z

Source-reported events for the cited work

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Observation cae45dd3-c846-412b-9054-78c4b9ae8bc7 · outbound

This paper cites Generative adversarial nets.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Generative adversarial nets

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.355481Z

Source-reported events for the cited work

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Observation 4bd02f51-5a7a-4325-9a76-fe918dbdbc22 · outbound

This paper cites Deep residual learning for image recognition.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Deep residual learning for image recognition

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.331845Z

Source-reported events for the cited work

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Observation 6a56c6bc-94ba-4635-9bf3-27af5346f102 · outbound

This paper cites Datadream: Few-shot guided dataset generation.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Datadream: Few-shot guided dataset generation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.311715Z

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Observation 658bd9cd-d1db-4040-be76-76e175fbdf1d · outbound

This paper cites A single-cell morphological dataset of leuko- cytes from aml patients and non-malignant controls.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics A single-cell morphological dataset of leuko- cytes from aml patients and non-malignant controls

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.289839Z

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 5fe2fbcc-42ee-455a-a481-b11716ad15f2 · outbound

This paper cites Synthetic data generation methods in healthcare: A review on open-source tools and methods.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Synthetic data generation methods in healthcare: A review on open-source tools and methods

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.269328Z

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 740ec339-1b1a-484a-8284-36fd9403a9ac · outbound

This paper cites Sdxl: Improving latent diffusion models for high-resolution image synthesis.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Sdxl: Improving latent diffusion models for high-resolution image synthesis

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.251059Z

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 2c25674b-23c8-4e73-8aaf-d4fca80ebaf9 · outbound

This paper cites Learning transferable visual models from natural language supervision.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Learning transferable visual models from natural language supervision

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.233959Z

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 1ea0425d-9ba8-4f4f-9172-72ee6b741da1 · outbound

This paper cites The future of digital health with federated learning.NPJ dig- ital medicine, 3(1):119, 2020.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics The future of digital health with federated learning.NPJ dig- ital medicine, 3(1):119, 2020

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.213848Z

Source-reported events for the cited work

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Observation 938a05a1-10d6-4b71-9356-196c76823450 · outbound

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

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics High-resolution image syn- thesis with latent diffusion models

Reference 14

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Source-reported events for the cited work

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Observation bea1583b-501a-4132-b7de-717e5354f28c · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 15

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Observation fd0eea84-ef45-41f9-87e9-97568df15eca · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Photorealistic text-to-image diffusion models with deep language understanding

Reference 16

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Observation 5f642c0e-4811-438c-b1af-6e9b27d16ee5 · outbound

This paper cites Synthetic data boosts medical foundation models.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Synthetic data boosts medical foundation models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.154832Z

Source-reported events for the cited work

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Observation a26ba142-cf45-4c9c-ae0f-2acb3df0f753 · outbound

This paper cites A data-efficient strategy for building high-performing medical foundation models.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics A data-efficient strategy for building high-performing medical foundation models

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.135370Z

Source-reported events for the cited work

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Observation 07fadb33-bfd3-4eb8-a812-ab8194e5cbc6 · outbound

This paper cites ViCTr: Vital Consistency Transfer for Pathology Aware Image Synthesis.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics ViCTr: Vital Consistency Transfer for Pathology Aware Image Synthesis

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:36:47.016727Z

Source-reported events for the cited work

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Observation a4681f03-35f6-477d-877f-8d016c74b7a5 · outbound

This paper cites Imbalanced domain generalization for robust single cell classification in hematological cytomorphology.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Imbalanced domain generalization for robust single cell classification in hematological cytomorphology

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.117351Z

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 e4913125-b52e-4bff-9c73-efcaed858ea9 · outbound

This paper cites Artificial intelligence in hematological diagnostics: Game changer or gadget? Blood Reviews, page 101019, 2022.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Artificial intelligence in hematological diagnostics: Game changer or gadget? Blood Reviews, page 101019, 2022

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.100592Z

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 ef63b6cb-e3d9-4293-9ca3-dddf88f5f98f · outbound

This paper cites A pragmatic note on evaluating generative models with fr \’echet incep- tion distance for retinal image synthesis.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics A pragmatic note on evaluating generative models with fr \’echet incep- tion distance for retinal image synthesis

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T19:36:46.879396Z

Source-reported events for the cited work

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Observation 6273e4f4-aaa0-488e-817a-ec3661fd159b · outbound

This paper cites Synaug: Exploiting synthetic data for data imbalance problems.

CytoDiff: AI-Driven Cytomorphology Image Synthesis for Medical Diagnostics Synaug: Exploiting synthetic data for data imbalance problems

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:47.082753Z

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

No inbound Pith citation observations are available.