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Paper Citation Record · LEDGER

Fairlearn: Assessing and Improving Fairness of AI Systems

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2303.16626.

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

pith.paper-citation-record.v1
2303.16626 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:40:53.002313Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:40:54.047518Z

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 f629e228-bf2a-4b1d-9341-64d13bbd7bab · inbound

Advancing Responsible Innovation in Agentic AI: A study of Ethical Frameworks for Household Automation cites this paper.

Advancing Responsible Innovation in Agentic AI: A study of Ethical Frameworks for Household Automation Fairlearn: Assessing and Improving Fairness of AI Systems

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:40:54.094168Z

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.

source=pdf_text observed=2026-08-06T15:40:53.002313Z digest=sha256:b5712666011f9075efd6edfcadcaaecd7d6ccc172700f17dc36dd6a91d63b739

Observation ac165237-b18e-47c5-8193-61732717f629 · inbound

FairDiffuseVQVAE: Sampling-Time Fairness in Tabular Diffusion via Conditional Refinement of Vector-Quantized Latents cites this paper.

FairDiffuseVQVAE: Sampling-Time Fairness in Tabular Diffusion via Conditional Refinement of Vector-Quantized Latents Fairlearn: Assessing and Improving Fairness of AI Systems

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-03T16:50:39.183180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T16:50:39.183180Z digest=sha256:0f2f4338d12d9cc74f915af8f29eb9db1bb618291b5796180c53d6cbef08d1ab