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Paper Citation Record · LEDGER

Modeling Techniques for Machine Learning Fairness: A Survey

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2111.03015.

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

pith.paper-citation-record.v1
2111.03015 v2

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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:31:49.566065Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T05:31:49.670547Z

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 b3d85ecb-3c66-4247-a84a-cd3edda78582 · inbound

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms cites this paper.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Modeling Techniques for Machine Learning Fairness: A Survey

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-12T05:31:49.676883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:31:49.566065Z digest=sha256:b6a6b62a1ac820aa8ce20efc3f2fd75f6d04a2d7f1a78823c7fed98681592f4e

Observation 4caf2bfa-6340-46eb-8e53-29d667fc0537 · 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 Modeling Techniques for Machine Learning Fairness: A Survey

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-03T16:50:39.073653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T16:50:39.073653Z digest=sha256:7da739c630a8677b5a766b4229f716b3744eba9a6da57671ed9f4f8822cb9b11