Pith. sign in

Paper Citation Record · LEDGER

General Post-Processing Framework for Fairness Adjustment of Machine Learning Models

As of 18 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 0 inbound Pith citation observations for arXiv:2504.16238.

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

pith.paper-citation-record.v1
2504.16238 v1

Coverage vector

measured 2 of 2 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:13:39.085554Z

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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

2 of 2 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d0fe5088-319e-40c0-9fde-37b0d9805204 · outbound

This paper cites Bias Mitigation Post-processing for Individual and Group Fairness.

General Post-Processing Framework for Fairness Adjustment of Machine Learning Models Bias Mitigation Post-processing for Individual and Group Fairness

Reference 2012

Resolution
metadata mismatch
local_arxiv, observed 2026-08-16T11:13:39.131233Z

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=2026-08-16T11:13:39.085554Z digest=sha256:983f3341a6dec9571bb149068ea1d43f10bd87378bd9b232c164e42a1b5bb1a1

Observation c53ff44f-c900-4459-ba8f-5e48b4cd4b8a · outbound

This paper cites AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias.

General Post-Processing Framework for Fairness Adjustment of Machine Learning Models AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-16T11:13:39.050879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:13:39.050879Z digest=sha256:051a921880c050de0499d66edff84de184927be154e3e808ab0c3d60986dff15

Pith citing papers

No inbound Pith citation observations are available.