Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
OpenBias: Open-set Bias Detection in Text-to-Image Generative Models
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2404.07990.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T12:13:24.322960Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T14:01:03.858727Z
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 0c5a27ae-7506-4593-90d9-5c337b00ca9f · inbound
POET: Supporting Prompting Creativity and Personalization with Automated Expansion of Text-to-Image Generation cites this paper.
POET: Supporting Prompting Creativity and Personalization with Automated Expansion of Text-to-Image Generation OpenBias: Open-set Bias Detection in Text-to-Image Generative Models
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T12:13:24.322960Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f21ee72e-13af-4ca6-9a83-c317f6e3f887 · inbound
DIMCIM: A Quantitative Evaluation Framework for Default-mode Diversity and Generalization in Text-to-Image Generative Models cites this paper.
DIMCIM: A Quantitative Evaluation Framework for Default-mode Diversity and Generalization in Text-to-Image Generative Models OpenBias: Open-set Bias Detection in Text-to-Image Generative Models
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:30:27.458273Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 42a0934a-c630-4bf3-bfb9-a22f150a88bf · inbound
Who Defines Fairness? Target-Based Prompting for Demographic Representation in Generative Models cites this paper.
Who Defines Fairness? Target-Based Prompting for Demographic Representation in Generative Models OpenBias: Open-set Bias Detection in Text-to-Image Generative Models
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:01:03.862739Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.