Paper Citation Record · LEDGER

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance?

As of 13 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2411.17374.

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

pith.paper-citation-record.v1
2411.17374 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:19:14.986679Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

18 of 18 outbound references displayed

verified exact0
verified fuzzy15
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8ac41b1e-d9ce-48a5-a3b4-1986b10a2c51 · outbound

This paper cites In: Proc.

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? In: Proc

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.356014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7281524c-719b-442a-991c-69033d5ac29d · outbound

This paper cites an unresolved cited work.

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:19:15.338462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0264b7af-992c-486e-814f-25150889aee6 · outbound

This paper cites Science356(6334), 183–186 (2017).

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? Science356(6334), 183–186 (2017)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T12:19:14.901411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65633a11-3788-4d02-9bc9-366336188d8b · outbound

This paper cites ACM CSUR56(7), 1–38 (2024).

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? ACM CSUR56(7), 1–38 (2024)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.281422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e0db90ee-8773-4f02-bcb6-795a6099f67c · outbound

This paper cites In: Proc.

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? In: Proc

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.258716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a32fed1d-556a-4fe3-9288-e44dc88810f2 · outbound

This paper cites In: Proc.

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? In: Proc

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.243810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0a0aa464-0e65-4962-9747-7cfbf7b29533 · outbound

This paper cites ACM TiST14(5), 1–48 (2023).

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? ACM TiST14(5), 1–48 (2023)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.230142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9bd639b3-26c3-4658-9f14-09fe6fec6ad3 · outbound

This paper cites In: Proc.

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? In: Proc

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.211314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c4e91b3a-2bfd-4e29-b414-1d5c0d7e67cc · outbound

This paper cites O’Reilly (2020).

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? O’Reilly (2020)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.196596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d5fb6cdb-79e4-48d2-809b-81920ee9f2f3 · outbound

This paper cites In: Proc.

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? In: Proc

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.176697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0075c0c9-be0e-40dc-848c-5f83cefe6998 · outbound

This paper cites ACM CSUR54(6), 1–35 (2021).

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? ACM CSUR54(6), 1–35 (2021)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.158930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4091f0c7-290c-405c-9ee7-229a3e6c573a · outbound

This paper cites an unresolved cited work.

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:19:15.145892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 42c91a43-1383-46eb-be00-bca2007cd395 · outbound

This paper cites In: Proc.

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? In: Proc

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.131657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 77d6ad63-14d7-42bc-92bf-a94532303fdd · outbound

This paper cites Expert Systems with Applications231, 120914 (2023).

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? Expert Systems with Applications231, 120914 (2023)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.114214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 513ae33c-894c-4458-ac59-f866efe9c936 · outbound

This paper cites In: Proc.

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? In: Proc

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.094928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 168249ba-92db-4f1c-a018-91b575e9e55f · outbound

This paper cites ACM TOIS41(3), 1–43 (2023).

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? ACM TOIS41(3), 1–43 (2023)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.078427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4968e4ec-2bdc-48ec-8042-8212d7cf164d · outbound

This paper cites In: Proc.

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? In: Proc

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.063436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 87e0b400-7bc8-4c3a-a419-048d3c424ef5 · outbound

This paper cites Oxford Review of Education36(3), 307–323 (2010).

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? Oxford Review of Education36(3), 307–323 (2010)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:19:15.039102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.