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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 2026-08-13T06:32:02.005865+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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.884834Z digest=sha256:790032da78cbf63988eae39777e68a13ff02447ee4eabc9322aa411685790c05

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.892600Z digest=sha256:f58e18678e05d032432376d67acf7499f932d475b7b52bcb904d765371e39d6f

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.

source=pdf_text observed=2026-08-12T12:19:14.901411Z digest=sha256:969a0b9258bd8ebd824ef17c7538aaaa513e104b82aff573658f1493f3baedcf

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.912554Z digest=sha256:b27e52b32400f6f736cfa90ecb529226486e2318be2e3c1197224697a7508ea0

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.918393Z digest=sha256:fcd095ed95def3a43f82aff910485353d04194a647af299958b6144f7f02b2cf

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.924070Z digest=sha256:e23df85617c219761acd5212e9ad5c1a54815a1c7a69b9591933d49bd714ba7a

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.930590Z digest=sha256:53a17ba7239edc1d61cfb693af8cc38568cfad77cb2fb0bc35f86abbdda3cb62

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.938111Z digest=sha256:2b11340045d1ab98766417f98e13029f0df63961cd869c987ba303a9561949d2

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.942373Z digest=sha256:9201627dc2014ed77afb33d5e1855ad465bc73767b58ebaa0fd4e5e0c2af380a

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.947083Z digest=sha256:e08ebe030c850e7df0a80ea451899c521b8ac149dcf917e8d5e43dcd140a137a

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.951520Z digest=sha256:e90798f241f64f54252a5837d7137e3eb885619942ea85155acbc56dca1631e1

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.956060Z digest=sha256:4af555e36348fffaf0070f67581bc3c85ca5b7598bb1001e1d244ebe88ae151a

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.960714Z digest=sha256:70c0f3cbbaea93fdef02e90c908b5f6acbb5b6f8e362c7b68c0a9faf92391e3e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.965374Z digest=sha256:04b67c563a03455dd666800dbfa05c405f52ef86cd60cb5550797b3a818473ea

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.970620Z digest=sha256:297ae41a3136ea7986113e544a5bc553061da05490a46d6e513cec141c1523b8

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.975394Z digest=sha256:746e5bede3e6be6086a5f6a74ac7f86070e3031016991d48bbc6f43067f3700a

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.979349Z digest=sha256:15d982118551916b56850aa2d67b1c52fae5c6f6ab2a6fda80d7e94dd2709e68

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T12:19:14.986679Z digest=sha256:d241fd19f1e065574feb1ee7e2efd8944e6157902db1ee462958bc4c4fbf4679

Pith citing papers

No inbound Pith citation observations are available.