Paper Citation Record · LEDGER

Achieving Group Fairness through Independence in Predictive Process Monitoring

As of 21 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 3 inbound Pith citation observations for arXiv:2412.04914.

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

pith.paper-citation-record.v1
2412.04914 v3

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:15:12.806892Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:30:15.571193Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T15:17:39.860584Z

Reference resolution

48 of 48 outbound references displayed

verified exact3
verified fuzzy29
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External citation measurements

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Outbound references

Observation 99192ca0-d87a-42f3-814b-66ed67040ca7 · outbound

This paper cites MIT Press (2023).

Achieving Group Fairness through Independence in Predictive Process Monitoring MIT Press (2023)

Reference 1

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Observation fd007238-65ca-4b7c-82e7-2542d05e6d81 · outbound

This paper cites Cambridge university press (2004).

Achieving Group Fairness through Independence in Predictive Process Monitoring Cambridge university press (2004)

Reference 2

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This paper cites In: Business Process Management, pp.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Business Process Management, pp

Reference 3

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Observation 887372d3-7e44-4b12-abca-9031d87a8d6f · outbound

This paper cites In: Proceedings of the Conference on Fairness, Accountability, and Transparency, p.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Proceedings of the Conference on Fairness, Accountability, and Transparency, p

Reference 4

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This paper cites In: Proceedings of the 23rd acm sigkdd interna- tional conference on knowledge discovery and data mining, pp.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Proceedings of the 23rd acm sigkdd interna- tional conference on knowledge discovery and data mining, pp

Reference 5

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Observation 02e6387d-12d8-48dc-af7e-bc4c7878e240 · outbound

This paper cites Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances.

Achieving Group Fairness through Independence in Predictive Process Monitoring Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances

Reference 6

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Achieving Group Fairness through Independence in Predictive Process Monitoring Unresolved cited work

Reference 7

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This paper cites IEEE Transactions on Services Computing12(6), 896–909 (2019),https://doi.org/10.1109/TSC.2016.2645153.

Achieving Group Fairness through Independence in Predictive Process Monitoring IEEE Transactions on Services Computing12(6), 896–909 (2019),https://doi.org/10.1109/TSC.2016.2645153

Reference 8

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This paper cites In: Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, p.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, p

Reference 9

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Achieving Group Fairness through Independence in Predictive Process Monitoring Unresolved cited work

Reference 10

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This paper cites Journal of Machine Learning Research13(25), 723–773 (2012), URL http://jmlr.org/papers/v13/gretton12a.html.

Achieving Group Fairness through Independence in Predictive Process Monitoring Journal of Machine Learning Research13(25), 723–773 (2012), URL http://jmlr.org/papers/v13/gretton12a.html

Reference 11

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Observation b91182ba-f8db-4f37-8688-4e4c8b309612 · outbound

This paper cites In: Precup, D., Teh, Y.W.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Precup, D., Teh, Y.W

Reference 12

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Observation 1ed762c6-9d35-4c10-9f4a-a90fde484194 · outbound

This paper cites Transactions on Machine Learning Research (2023), ISSN 2835-8856.

Achieving Group Fairness through Independence in Predictive Process Monitoring Transactions on Machine Learning Research (2023), ISSN 2835-8856

Reference 13

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This paper cites Neural Comput.

Achieving Group Fairness through Independence in Predictive Process Monitoring Neural Comput

Reference 14

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Observation b388325f-897e-407b-8b25-3b5c083b1443 · outbound

This paper cites In: Proceedings of the 39th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Proceedings of the 39th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol

Reference 15

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Achieving Group Fairness through Independence in Predictive Process Monitoring Unresolved cited work

Reference 16

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Observation c27cca32-07c0-427f-a545-22bd86a7fdac · outbound

This paper cites Inherent Trade-Offs in the Fair Determination of Risk Scores.

Achieving Group Fairness through Independence in Predictive Process Monitoring Inherent Trade-Offs in the Fair Determination of Risk Scores

Reference 17

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Observation e36a0669-1ce9-4998-9456-afd09b1816e6 · outbound

This paper cites Business & Information Systems Engineering63(3), 261–276 (2021).

Achieving Group Fairness through Independence in Predictive Process Monitoring Business & Information Systems Engineering63(3), 261–276 (2021)

Reference 18

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Observation c11be0e7-cb1d-4ddf-8ff7-1e89941e7ae0 · outbound

This paper cites Achieving Fairness in Predictive Process Analytics via Adversarial Learning (Extended Version).

Achieving Group Fairness through Independence in Predictive Process Monitoring Achieving Fairness in Predictive Process Analytics via Adversarial Learning (Extended Version)

Reference 19

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This paper cites Decoupled Weight Decay Regularization.

Achieving Group Fairness through Independence in Predictive Process Monitoring Decoupled Weight Decay Regularization

Reference 20

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This paper cites ACM SIGKDD Explorations Newsletter23(1), 14–23 (2021).

Achieving Group Fairness through Independence in Predictive Process Monitoring ACM SIGKDD Explorations Newsletter23(1), 14–23 (2021)

Reference 21

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Observation e090b34f-0c84-4a98-a06d-db629e572fa0 · outbound

This paper cites In: Process Mining Workshops, Springer Nature Switzerland, Cham (2025).

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Process Mining Workshops, Springer Nature Switzerland, Cham (2025)

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:15:13.394723Z

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Observation e22151a0-bce9-4397-8fd2-817e13df1dc6 · outbound

This paper cites Advances in Applied Probability 29(2), 429–443 (1997), https://doi.org/10.2307/1428011.

Achieving Group Fairness through Independence in Predictive Process Monitoring Advances in Applied Probability 29(2), 429–443 (1997), https://doi.org/10.2307/1428011

Reference 23

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Achieving Group Fairness through Independence in Predictive Process Monitoring Unresolved cited work

Reference 24

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This paper cites In: Process Mining Workshops, pp.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Process Mining Workshops, pp

Reference 25

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Observation 9f0dc563-be74-4e7a-b050-475bda1fa61e · outbound

This paper cites In: Process Mining Workshops, pp.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Process Mining Workshops, pp

Reference 26

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Achieving Group Fairness through Independence in Predictive Process Monitoring Unresolved cited work

Reference 27

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Observation 9ccc128b-236b-40a0-844b-ba45edbf9bdf · outbound

This paper cites A Collection of Simulated Event Logs for Fairness Assessment in Process Mining.

Achieving Group Fairness through Independence in Predictive Process Monitoring A Collection of Simulated Event Logs for Fairness Assessment in Process Mining

Reference 28

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This paper cites In: Process Mining Workshops, pp.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Process Mining Workshops, pp

Reference 29

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This paper cites In: On the Move to Meaningful Internet Systems: OTM 2019 Conferences, pp.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: On the Move to Meaningful Internet Systems: OTM 2019 Conferences, pp

Reference 30

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Observation 17dc2774-0619-4a21-bc36-c553e58ed384 · outbound

This paper cites Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)8274 LNCS, 389–403 (2013).

Achieving Group Fairness through Independence in Predictive Process Monitoring Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)8274 LNCS, 389–403 (2013)

Reference 31

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Observation cf1491a6-1c94-41b0-9615-c685e66be83f · outbound

This paper cites Annals of Mathematical Statistics27, 832–837 (1956).

Achieving Group Fairness through Independence in Predictive Process Monitoring Annals of Mathematical Statistics27, 832–837 (1956)

Reference 32

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Observation 53cdc95a-b188-4a26-8a15-79e49a928ff5 · outbound

This paper cites In: Proceedings of the 34th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Proceedings of the 34th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol

Reference 33

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This paper cites In: Comuzzi, M., Grigori, D., Sellami, M., Zhou, Z.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Comuzzi, M., Grigori, D., Sellami, M., Zhou, Z

Reference 34

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This paper cites International Symposium on Data-Driven Process Discovery and Analysis pp.

Achieving Group Fairness through Independence in Predictive Process Monitoring International Symposium on Data-Driven Process Discovery and Analysis pp

Reference 35

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This paper cites Electronic Journal of Statistics 6(none), 1550 – 1599 (2012), https://doi.org/10.1214/12-EJS722.

Achieving Group Fairness through Independence in Predictive Process Monitoring Electronic Journal of Statistics 6(none), 1550 – 1599 (2012), https://doi.org/10.1214/12-EJS722

Reference 36

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This paper cites On integral probability metrics, \phi-divergences and binary classification.

Achieving Group Fairness through Independence in Predictive Process Monitoring On integral probability metrics, \phi-divergences and binary classification

Reference 37

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Achieving Group Fairness through Independence in Predictive Process Monitoring In: International Conference on Advanced Information Systems Engineering, pp

Reference 38

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Observation 8052f939-4ff0-42c2-9994-5e6271297d11 · outbound

This paper cites TKDD13(2), 17:1–17:57 (2019).

Achieving Group Fairness through Independence in Predictive Process Monitoring TKDD13(2), 17:1–17:57 (2019)

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:15:13.320090Z

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Observation 3a0d3ea1-e042-450f-8fd9-df18fd70cea8 · outbound

This paper cites Information Systems36(2), 450–475 (2011), ISSN 03064379.

Achieving Group Fairness through Independence in Predictive Process Monitoring Information Systems36(2), 450–475 (2011), ISSN 03064379

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:15:13.313466Z

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Observation 43b8bb0d-7fb8-49fc-9ea9-7774cb79125e · outbound

This paper cites Information Sciences594, 400–415 (2022) Achieving Group F airness through Independence in PPM 19.

Achieving Group Fairness through Independence in Predictive Process Monitoring Information Sciences594, 400–415 (2022) Achieving Group F airness through Independence in PPM 19

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:15:13.306765Z

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This paper cites ACM Transactions on Intelligent Systems and Technology (TIST)10(4), 1–34 (2019).

Achieving Group Fairness through Independence in Predictive Process Monitoring ACM Transactions on Intelligent Systems and Technology (TIST)10(4), 1–34 (2019)

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:15:13.299873Z

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Observation 35a306f9-e67f-467e-9d67-aba0912616b5 · outbound

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Achieving Group Fairness through Independence in Predictive Process Monitoring Unresolved cited work

Reference 43

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Achieving Group Fairness through Independence in Predictive Process Monitoring Springer Texts in Statistics, Springer New York (2006), ISBN 9780387306230, URL https://books.google.be/books?id=MRFlzQfRg7UC

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:15:13.288713Z

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Observation 88b16c06-66c9-4912-8272-b3075bc3ae6f · outbound

This paper cites In: Business Process Management Workshops, pp.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Business Process Management Workshops, pp

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:15:13.280964Z

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Observation 03dea4b9-5b44-447c-a156-d3c4119d9d72 · outbound

This paper cites In: 2024 6th International Conference on Process Mining (ICPM), pp.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: 2024 6th International Conference on Process Mining (ICPM), pp

Reference 46

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This paper cites In: Proceedings of the 30th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Proceedings of the 30th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:15:13.274073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 816fa4f1-7959-4166-a47c-76be9a65eac8 · outbound

This paper cites In: Advances in Neural Information Processing Systems, vol.

Achieving Group Fairness through Independence in Predictive Process Monitoring In: Advances in Neural Information Processing Systems, vol

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:15:13.267293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation c96cca26-9271-4977-9a51-05887e4122cd · inbound

Decision-centric fairness: Evaluation and optimization for resource allocation problems cites this paper.

Decision-centric fairness: Evaluation and optimization for resource allocation problems Achieving Group Fairness through Independence in Predictive Process Monitoring

Reference 12

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T2I-ReasonBench: Benchmarking Reasoning-Informed Text-to-Image Generation cites this paper.

T2I-ReasonBench: Benchmarking Reasoning-Informed Text-to-Image Generation Achieving Group Fairness through Independence in Predictive Process Monitoring

Reference 24

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Observation 891b09c0-15aa-468e-821c-0455ff8072f5 · inbound

FairLoop: Software Support for Human-Centric Fairness in Predictive Business Process Monitoring cites this paper.

FairLoop: Software Support for Human-Centric Fairness in Predictive Business Process Monitoring Achieving Group Fairness through Independence in Predictive Process Monitoring

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-05T15:17:39.866739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.