Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2305.06969.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T18:32:49.519436Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-09T05:50:28.344451Z
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 aecaf25a-b2c4-4b0a-a3b6-6b9b901c574f · inbound
Generalized Venn and Venn-Abers Calibration with Applications in Conformal Prediction cites this paper.
Generalized Venn and Venn-Abers Calibration with Applications in Conformal Prediction A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:32:49.519436Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 63162e01-5fe7-44f1-a946-f6ee07403225 · inbound
Investigating Intersectional Bias in Large Language Models using Confidence Disparities in Coreference Resolution cites this paper.
Investigating Intersectional Bias in Large Language Models using Confidence Disparities in Coreference Resolution A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:21:05.784489Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7533fed-29d9-4162-a24f-66cbe0059208 · inbound
Toward Fair Speech Technologies: A Comprehensive Survey of Bias and Fairness in Speech AI cites this paper.
Toward Fair Speech Technologies: A Comprehensive Survey of Bias and Fairness in Speech AI A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges
Reference 127
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T05:50:28.346181Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.