Paper Citation Record · LEDGER

Survey on Causal-based Machine Learning Fairness Notions

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2010.09553.

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

pith.paper-citation-record.v1
2010.09553 v7

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:52:36.334992Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T10:03:17.050519Z

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 62006ae3-24be-4262-b00d-cb3acadd88f1 · inbound

Software Fairness: An Analysis and Survey cites this paper.

Software Fairness: An Analysis and Survey Survey on Causal-based Machine Learning Fairness Notions

Reference 98

Resolution: verified exact; arxiv_id, observed 2026-05-24T12:06:10.972996Z

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.

Observation f7461a03-9976-449d-a5c8-0a1061c6a40f · inbound

Exploring Fairness Interventions in Open Source Projects cites this paper.

Exploring Fairness Interventions in Open Source Projects Survey on Causal-based Machine Learning Fairness Notions

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T18:52:36.334992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fbaa55e-d1b8-4775-9b6f-6e342f8f7874 · inbound

Exploring the Landscape of Fairness Interventions in Software Engineering cites this paper.

Exploring the Landscape of Fairness Interventions in Software Engineering Survey on Causal-based Machine Learning Fairness Notions

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.829399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85316e35-79e1-4498-a326-a061e762cb9e · inbound

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants cites this paper.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Survey on Causal-based Machine Learning Fairness Notions

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:57.194673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc2f43ea-dffe-4540-8cba-c5abc2e5cd10 · inbound

Counterfactually Fair Regression via Optimal Transport cites this paper.

Counterfactually Fair Regression via Optimal Transport Survey on Causal-based Machine Learning Fairness Notions

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-06-29T10:03:17.051923Z

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.