Paper Citation Record · LEDGER

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces

As of 22 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2608.13455.

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

pith.paper-citation-record.v1
2608.13455 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:39:58.888410Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

22 of 22 outbound references displayed

verified exact1
verified fuzzy2
unresolved15
parse uncertain0
malformed identifier3
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8c82324c-78d7-498b-82cc-ccdbe7669795 · outbound

This paper cites et al.: The UK Biobank resource with deep phe- notyping and genomic data.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces et al.: The UK Biobank resource with deep phe- notyping and genomic data

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.789828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28498fed-561c-4f4b-a5b1-bfaa2a50dca6 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.794829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95066b3a-d1bc-4663-8037-8502f68342ab · outbound

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

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.799948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91ad5df1-c693-4770-bb28-f9f784c6830b · outbound

This paper cites Scaling Rectified Flow Transformers for High-Resolution Image Synthesis.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces Scaling Rectified Flow Transformers for High-Resolution Image Synthesis

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.804777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43870963-72f6-48e2-a67d-47f355fe0751 · outbound

This paper cites Adapting Self-Supervised Representations as a Latent Space for Efficient Generation.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces Adapting Self-Supervised Representations as a Latent Space for Efficient Generation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.809886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21d0602b-7eb0-4dbd-85dc-493890147963 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces Deep Residual Learning for Image Recognition

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.819486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8e46866-9c66-4525-ab14-7dc4a08a6cc4 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces Classifier-Free Diffusion Guidance

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.823924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1863ebb9-1491-4384-a42b-e2002e66800d · outbound

This paper cites et al.: PRETI: Patient-Aware Retinal Foundation Model via Metadata-Guided Representation Learning.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces et al.: PRETI: Patient-Aware Retinal Foundation Model via Metadata-Guided Representation Learning

Reference 9

Resolution: verified exact; doi, observed 2026-08-14T10:39:58.989890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T20:38:18.472866+00:00.

Observation 4b1a99d8-41a7-49fb-a0f3-b856c10458b5 · outbound

This paper cites Flow Matching for Generative Modeling.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces Flow Matching for Generative Modeling

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.833452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9856841-ce1f-4431-977a-8f053421056b · outbound

This paper cites https://doi.org/10.1038/s41586- 025-09079-8, https://www.nature.com/articles/s41586-025-09079-8.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces https://doi.org/10.1038/s41586- 025-09079-8, https://www.nature.com/articles/s41586-025-09079-8

Reference 11

Resolution: malformed identifier; no resolver link, observed 2026-08-14T10:39:58.837639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9fd7aef-4a2a-4260-bbed-aabe35e96534 · outbound

This paper cites npj Imaging 2026 (5 2026).

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces npj Imaging 2026 (5 2026)

Reference 12

Resolution: malformed identifier; doi_truncated, observed 2026-08-14T10:39:58.967500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1c4cbaef-9d65-4e9f-9168-c96372f976c9 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces Learning Transferable Visual Models From Natural Language Supervision

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.846960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bed88dc-88ae-45d2-9010-d448855661a7 · outbound

This paper cites et al.: High-Resolution Image Synthesis with Latent Dif- fusion Models.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces et al.: High-Resolution Image Synthesis with Latent Dif- fusion Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.851107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e52f33c4-0195-4ec5-9540-bb171b72eee5 · outbound

This paper cites et al.: A Foundation Language-Image Model of the Retina (FLAIR): encoding expert knowledge in text supervision.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces et al.: A Foundation Language-Image Model of the Retina (FLAIR): encoding expert knowledge in text supervision

Reference 15

Resolution: metadata mismatch; raw_fallback, observed 2026-08-14T10:39:59.118118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 88e4fe87-45ff-4d9d-82af-b8b25af9817b · outbound

This paper cites In: Annual Confer- ence on Medical Image Understanding and Analysis.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces In: Annual Confer- ence on Medical Image Understanding and Analysis

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:59.311854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d4a40aca-1ebc-462b-823f-87971a9afb47 · outbound

This paper cites In: ICLR 2021 - 9th International Conference on Learning Representations (2021).

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces In: ICLR 2021 - 9th International Conference on Learning Representations (2021)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:59.298832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7b370fae-95cd-420c-b8d1-ea1ccb7e0edc · outbound

This paper cites et al.: Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces et al.: Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.866955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51df6c22-dd1b-43ca-bb17-dd707ba67634 · outbound

This paper cites MLP-Mixer: An all-MLP Architecture for Vision.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces MLP-Mixer: An all-MLP Architecture for Vision

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.871054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 115f9436-c829-43ae-b4de-d8d1e2310325 · outbound

This paper cites BrainDINO: A Brain MRI Foundation Model for Generalizable Clinical Representation Learning.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces BrainDINO: A Brain MRI Foundation Model for Generalizable Clinical Representation Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.875264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fbe79a2-38ee-49ea-bdfc-01803b57f866 · outbound

This paper cites et al.: UrFound: Towards Universal Retinal Foundation Models via Knowledge-Guided Masked Modeling.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces et al.: UrFound: Towards Universal Retinal Foundation Models via Knowledge-Guided Masked Modeling

Reference 21

Resolution: malformed identifier; doi_truncated, observed 2026-08-14T10:39:58.944530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3e8a7748-4673-45e8-b404-170e564a2891 · outbound

This paper cites et al.: A foundation model for generalizable disease de- tection from retinal images.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces et al.: A foundation model for generalizable disease de- tection from retinal images

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.883673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da5f380d-a0af-418d-91c8-79189d3b5782 · outbound

This paper cites et al.: AutoMorph: Automated Retinal Vascular Morphology Quantification Via a Deep Learning Pipeline.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces et al.: AutoMorph: Automated Retinal Vascular Morphology Quantification Via a Deep Learning Pipeline

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:58.888410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.