Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T12:19:14.986679Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T12:19:14.986679Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
18 of 18 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 8ac41b1e-d9ce-48a5-a3b4-1986b10a2c51 · outbound
Reference 1
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.
Observation 7281524c-719b-442a-991c-69033d5ac29d · outbound
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? Unresolved cited work
Reference 2
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.
Observation 0264b7af-992c-486e-814f-25150889aee6 · outbound
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? Science356(6334), 183–186 (2017)
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 65633a11-3788-4d02-9bc9-366336188d8b · outbound
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? ACM CSUR56(7), 1–38 (2024)
Reference 4
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.
Observation e0db90ee-8773-4f02-bcb6-795a6099f67c · outbound
Reference 5
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.
Observation a32fed1d-556a-4fe3-9288-e44dc88810f2 · outbound
Reference 6
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.
Observation 0a0aa464-0e65-4962-9747-7cfbf7b29533 · outbound
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? ACM TiST14(5), 1–48 (2023)
Reference 7
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.
Observation 9bd639b3-26c3-4658-9f14-09fe6fec6ad3 · outbound
Reference 8
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.
Observation c4e91b3a-2bfd-4e29-b414-1d5c0d7e67cc · outbound
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? O’Reilly (2020)
Reference 9
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.
Observation d5fb6cdb-79e4-48d2-809b-81920ee9f2f3 · outbound
Reference 10
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.
Observation 0075c0c9-be0e-40dc-848c-5f83cefe6998 · outbound
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? ACM CSUR54(6), 1–35 (2021)
Reference 11
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.
Observation 4091f0c7-290c-405c-9ee7-229a3e6c573a · outbound
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? Unresolved cited work
Reference 12
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.
Observation 42c91a43-1383-46eb-be00-bca2007cd395 · outbound
Reference 13
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.
Observation 77d6ad63-14d7-42bc-92bf-a94532303fdd · outbound
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? Expert Systems with Applications231, 120914 (2023)
Reference 14
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.
Observation 513ae33c-894c-4458-ac59-f866efe9c936 · outbound
Reference 15
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.
Observation 168249ba-92db-4f1c-a018-91b575e9e55f · outbound
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? ACM TOIS41(3), 1–43 (2023)
Reference 16
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.
Observation 4968e4ec-2bdc-48ec-8042-8212d7cf164d · outbound
Reference 17
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.
Observation 87e0b400-7bc8-4c3a-a419-048d3c424ef5 · outbound
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance? Oxford Review of Education36(3), 307–323 (2010)
Reference 18
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.
No inbound Pith citation observations are available.