Paper Citation Record · LEDGER

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML

As of 14 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 1 inbound Pith citation observation for arXiv:2411.11101.

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

pith.paper-citation-record.v1
2411.11101 v2

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:58:53.847784Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T18:50:20.219579Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T18:51:30.542392Z

Reference resolution

19 of 19 outbound references displayed

verified exact0
verified fuzzy8
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3063fc1c-86a2-42d3-875f-b28321a17165 · outbound

This paper cites Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T18:58:53.762621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f05c6dd1-11fd-4650-a3ff-48bdb2723370 · outbound

This paper cites A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T18:58:53.796668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17df52e5-e84e-46b1-8f57-c331daf7b47e · outbound

This paper cites Gohar, S.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Gohar, S

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:58:54.096759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 37a0ff6c-286b-4b0e-b84f-2e0f56c33654 · outbound

This paper cites Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T18:58:53.810618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b0ebc72-3ccc-4099-95aa-299e9a15e404 · outbound

This paper cites an unresolved cited work.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-12T18:58:54.073735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1942bc6e-c51d-4e78-900c-7325e20288a7 · outbound

This paper cites Perrone, M.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Perrone, M

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:58:54.056959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7c001473-0af2-4be8-84ba-9b8f5d07f597 · outbound

This paper cites an unresolved cited work.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-12T18:58:54.024918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e4f684f3-4b00-4185-b9ac-69b87a36345c · outbound

This paper cites an unresolved cited work.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Unresolved cited work

Reference 1994

Resolution: unresolved; no resolver link, observed 2026-08-12T18:58:53.816971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb1118be-57c6-4234-a72c-3a5a4583c9d5 · outbound

This paper cites an unresolved cited work.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Unresolved cited work

Reference 1996

Resolution: unresolved; no resolver link, observed 2026-08-12T18:58:53.757609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2134bbfb-7016-4a32-93ab-25e7a25386bf · outbound

This paper cites an unresolved cited work.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Unresolved cited work

Reference 2000

Resolution: unresolved; no resolver link, observed 2026-08-12T18:58:53.746617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb90b6c8-9391-4b4d-9fa5-21c58703add1 · outbound

This paper cites an unresolved cited work.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Unresolved cited work

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-12T18:58:53.827322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e952aed-a60b-40f7-b3a4-e9e231921755 · outbound

This paper cites an unresolved cited work.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Unresolved cited work

Reference 2017

Resolution: unresolved; raw_fallback, observed 2026-08-12T18:58:54.176085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 94903212-092b-4170-8c18-3655a62966d5 · outbound

This paper cites [2023], we redirect the reader to their work and the FFB benchmark code 3 for details on the underlying setup.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML [2023], we redirect the reader to their work and the FFB benchmark code 3 for details on the underlying setup

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:58:54.005897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f9185050-9d67-4f7d-acae-1c1aa9c51c88 · outbound

This paper cites Your fairness may vary: Pretrained language model fairness in toxic text classification.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Your fairness may vary: Pretrained language model fairness in toxic text classification

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-12T18:58:53.752225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a77b74ec-fa5b-48d2-8f00-867d5b404d1f · outbound

This paper cites Black and M.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Black and M

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:58:54.160217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4a6f146d-3edf-445b-934f-bec5e1605a74 · outbound

This paper cites Black, M.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Black, M

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:58:54.144642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b02fe1fc-c563-4ce0-8765-09aa63da75ea · outbound

This paper cites Simson, F.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Simson, F

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:58:54.040908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cc84762a-68e6-4421-9685-65dcbd21cf22 · outbound

This paper cites Black, T.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Black, T

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:58:54.129260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d31d45cb-5d3c-4abc-8a26-1419d8be84c9 · outbound

This paper cites Ganesh, H.

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML Ganesh, H

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:58:54.113491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation bcac6d01-f24b-4a9d-86ec-0d9dbd503ec2 · inbound

Diagnostics for Individual-Level Prediction Instability in Machine Learning for Healthcare cites this paper.

Diagnostics for Individual-Level Prediction Instability in Machine Learning for Healthcare Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-15T18:51:30.545855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.