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Paper Citation Record · LEDGER

The Pursuit of Fairness in Artificial Intelligence Models: A Survey

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2403.17333.

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

pith.paper-citation-record.v1
2403.17333 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:37:45.811849Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

6
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 37264f38-9276-4966-98a6-36dd2d0cf4eb · inbound

ASCenD-BDS: Adaptable, Stochastic and Context-aware framework for Detection of Bias, Discrimination and Stereotyping cites this paper.

ASCenD-BDS: Adaptable, Stochastic and Context-aware framework for Detection of Bias, Discrimination and Stereotyping The Pursuit of Fairness in Artificial Intelligence Models: A Survey

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-09T13:29:57.203680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:29:57.203680Z digest=sha256:ecf39908f17a2906865f28fd74528c667f6f22a7e645bf0f3091f3a3d5a0a359

Observation 9ca9a963-88a1-4c45-90e8-8c9defeccea8 · inbound

The Process of Categorical Clipping at the Core of the Genesis of Concepts in Synthetic Neural Cognition cites this paper.

The Process of Categorical Clipping at the Core of the Genesis of Concepts in Synthetic Neural Cognition The Pursuit of Fairness in Artificial Intelligence Models: A Survey

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-10T17:37:45.811849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:37:45.811849Z digest=sha256:c96569689d39810cf19989533a4c06175d529e32bdd7a2645cabdc575eb71614

Observation 00ac2bc2-ae54-4353-9475-a4b93047ed6f · 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 The Pursuit of Fairness in Artificial Intelligence Models: A Survey

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-09T23:49:44.503448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-09T23:48:37.948835Z digest=sha256:01d85c4e7939c572f104ed8f061ac02f30a43fe735646a99098c994db3819544