Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Data
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2508.16783.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T18:05:36.761517Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T00:29:16.094087Z
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 a2984a03-d49a-4014-817a-e0ab11cb1938 · inbound
CompDiff: Hierarchical Compositional Diffusion for Fair and Zero-Shot Intersectional Medical Image Generation cites this paper.
CompDiff: Hierarchical Compositional Diffusion for Fair and Zero-Shot Intersectional Medical Image Generation Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Data
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:05:36.761517Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4fe64115-28a7-40e4-be78-7b3cad601369 · inbound
The Learnability Gap in Medical Latent Diffusion cites this paper.
The Learnability Gap in Medical Latent Diffusion Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Data
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T15:43:26.819672Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cf0efcbf-9d32-4cc0-aa94-23d5c2aa486b · inbound
Reputation Effects: Robustness and Fragility cites this paper.
Reputation Effects: Robustness and Fragility Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Data
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T16:38:52.791553Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e88fb644-0752-4b02-b884-adc0a3aaace2 · inbound
Reputation Effects: Robustness and Fragility cites this paper.
Reputation Effects: Robustness and Fragility Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Data
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T18:54:43.677073Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2d4f47a8-4168-4e96-8c86-d0455edac0ca · inbound
Scaling Generative Foundation Models for Chest Radiography with Rectified Flow Transformers cites this paper.
Scaling Generative Foundation Models for Chest Radiography with Rectified Flow Transformers Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Data
Reference 52
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T00:29:16.097413Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.