Paper Citation Record · LEDGER

Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2210.04133.

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

pith.paper-citation-record.v1
2210.04133 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:31:04.127533Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T04:13:52.885719Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b471c29e-5d93-435d-96c3-174c0a27435d · inbound

Data-Centric Foundation Models in Computational Healthcare: A Survey cites this paper.

Data-Centric Foundation Models in Computational Healthcare: A Survey Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-24T04:13:52.889405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 351e5cc4-7c84-4fca-a90f-85d6444a046e · inbound

Anatomy-Grounded Weakly Supervised Prompt Tuning for Chest X-ray Latent Diffusion Models cites this paper.

Anatomy-Grounded Weakly Supervised Prompt Tuning for Chest X-ray Latent Diffusion Models Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T04:31:04.127533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0714610d-567d-4e24-9942-64df32089db6 · inbound

Data Can Speak for Itself: Quality-guided Utilization of Wireless Synthetic Data cites this paper.

Data Can Speak for Itself: Quality-guided Utilization of Wireless Synthetic Data Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T21:54:48.302861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77f8dbde-7e36-4257-a5ab-192c56ded150 · inbound

Prompt Mechanisms in Medical Imaging: A Comprehensive Survey cites this paper.

Prompt Mechanisms in Medical Imaging: A Comprehensive Survey Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T22:02:24.765634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cd0727d-699f-4f74-a7b0-34aadd4dd0ee · inbound

CheXmix: Unified Generative Pretraining for Vision Language Models in Medical Imaging cites this paper.

CheXmix: Unified Generative Pretraining for Vision Language Models in Medical Imaging Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:16:09.743647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d747a289-e306-498d-ad80-44ccf468361a · inbound

Harm is not Universal: Community-Specific Toxicity Detection is Urgently Needed cites this paper.

Harm is not Universal: Community-Specific Toxicity Detection is Urgently Needed Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains

Reference 169

Resolution: unresolved; no resolver link, observed 2026-07-31T09:24:20.777441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.