Paper Citation Record · LEDGER

Algorithmic Fairness: A Runtime Perspective

As of 16 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2507.20711.

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

pith.paper-citation-record.v1
2507.20711 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:26:53.814422Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

49 of 49 outbound references displayed

verified exact0
verified fuzzy38
unresolved8
parse uncertain0
malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 07d51b19-463d-4fc9-b8da-20280c038c19 · outbound

This paper cites In: Proceedings of the International Conference on Machine Learning (ICML).

Algorithmic Fairness: A Runtime Perspective In: Proceedings of the International Conference on Machine Learning (ICML)

Reference 1

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Observation 37b3f795-b852-454f-8e37-f86876d2e7fe · outbound

This paper cites Proceedings of the ACM on Programming Lan- guages 1(OOPSLA), 1–30 (2017) Algorithmic Fairness: A Runtime Perspective 19.

Algorithmic Fairness: A Runtime Perspective Proceedings of the ACM on Programming Lan- guages 1(OOPSLA), 1–30 (2017) Algorithmic Fairness: A Runtime Perspective 19

Reference 2

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Observation f475fe8e-d304-4960-85ba-6b73af454829 · outbound

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

Algorithmic Fairness: A Runtime Perspective In: Proceedings of the Conference on Fairness, Accountability, and Transparency

Reference 3

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This paper cites Ab initio properties of the NaLi molecule in the $a^3\Sigma^+$ electronic state.

Algorithmic Fairness: A Runtime Perspective Ab initio properties of the NaLi molecule in the $a^3\Sigma^+$ electronic state

Reference 4

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Observation 359d8f74-90fa-4f98-ad0f-16112605d078 · outbound

This paper cites In: International Conference on Learning Representations (2021).

Algorithmic Fairness: A Runtime Perspective In: International Conference on Learning Representations (2021)

Reference 5

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Observation 79d33a6c-00e9-4643-8dd4-004c8da83df5 · outbound

This paper cites MIT Press (2023).

Algorithmic Fairness: A Runtime Perspective MIT Press (2023)

Reference 6

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Observation ca75f1aa-a036-42cc-a601-b878699347f9 · outbound

This paper cites In: Lectures on Runtime Verification, pp.

Algorithmic Fairness: A Runtime Perspective In: Lectures on Runtime Verification, pp

Reference 7

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Observation 9b1da491-85a6-4e0a-b329-2271881cbdcb · outbound

This paper cites Proceedings of the ACM on Programming Languages 3(OOPSLA), 1–27 (2019).

Algorithmic Fairness: A Runtime Perspective Proceedings of the ACM on Programming Languages 3(OOPSLA), 1–27 (2019)

Reference 8

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Observation afd4accd-0274-41dd-add0-4ee98c753de2 · outbound

This paper cites IBM Journal of Research and Development 63(4/5), 4–1 (2019).

Algorithmic Fairness: A Runtime Perspective IBM Journal of Research and Development 63(4/5), 4–1 (2019)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:26:54.755620Z

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Observation 7cdca5b2-16fe-43e0-a648-e8512fbd427b · outbound

This paper cites Sociological Methods & Research50(1), 3–44 (2021).

Algorithmic Fairness: A Runtime Perspective Sociological Methods & Research50(1), 3–44 (2021)

Reference 10

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Observation da63c80c-bb44-4a9f-91a1-6d256f00290b · outbound

This paper cites Microsoft, Tech.

Algorithmic Fairness: A Runtime Perspective Microsoft, Tech

Reference 11

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Observation 3de2cd82-1a6e-4a33-ba9f-13ef4585e067 · outbound

This paper cites In: International Conference on Formal Structures for Computation and Deduction (FSCD).

Algorithmic Fairness: A Runtime Perspective In: International Conference on Formal Structures for Computation and Deduction (FSCD)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:26:54.700775Z

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Observation 443b5d93-09f8-47f3-86b6-325d27890815 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence39(15), 15659–15668 (2025).

Algorithmic Fairness: A Runtime Perspective Proceedings of the AAAI Conference on Artificial Intelligence39(15), 15659–15668 (2025)

Reference 13

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Observation 02bc3cd5-3659-4137-a6ea-0c1e87411f85 · outbound

This paper cites In: Proceedings of the Conference on Fairness, Accountability, and Trans- parency (FAccT).

Algorithmic Fairness: A Runtime Perspective In: Proceedings of the Conference on Fairness, Accountability, and Trans- parency (FAccT)

Reference 14

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Observation f3363968-1638-4894-80d4-5d252d579681 · outbound

This paper cites In: International Conference on Formal Modeling and Analysis of Timed Systems.

Algorithmic Fairness: A Runtime Perspective In: International Conference on Formal Modeling and Analysis of Timed Systems

Reference 15

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Observation 7a5774be-df90-4237-ac79-4462453254bf · outbound

This paper cites Science advances 4(1), eaao5580 (2018).

Algorithmic Fairness: A Runtime Perspective Science advances 4(1), eaao5580 (2018)

Reference 16

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Observation 226926f6-487b-461c-92f1-7eded52b961c · outbound

This paper cites In: Proceedings of the 3rd Innovations in Theoretical Computer Science Con- ference (ITCS).

Algorithmic Fairness: A Runtime Perspective In: Proceedings of the 3rd Innovations in Theoretical Computer Science Con- ference (ITCS)

Reference 17

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Observation 24ccebd5-5de9-43f8-b8eb-d86b73a7be62 · outbound

This paper cites In: Proceedings of the 3rd innovations in theoretical computer science con- ference.

Algorithmic Fairness: A Runtime Perspective In: Proceedings of the 3rd innovations in theoretical computer science con- ference

Reference 18

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Observation fe4e7dc0-0126-4d64-a8f2-07947222d3dd · outbound

This paper cites Real-time Stream-based Monitoring.

Algorithmic Fairness: A Runtime Perspective Real-time Stream-based Monitoring

Reference 19

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This paper cites Algorithmic Fairness Verification with Graphical Models.

Algorithmic Fairness: A Runtime Perspective Algorithmic Fairness Verification with Graphical Models

Reference 20

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Observation 2f622532-837f-4f54-a595-e8aa2e863623 · outbound

This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).

Algorithmic Fairness: A Runtime Perspective In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)

Reference 21

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Observation 5995adfa-8624-4484-a52e-8758accf6b1d · outbound

This paper cites In: Advances in Neural Information Processing Systems (NeurIPS).

Algorithmic Fairness: A Runtime Perspective In: Advances in Neural Information Processing Systems (NeurIPS)

Reference 22

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Observation 5788264c-04a6-4cb7-929e-1ef2bb11d797 · outbound

This paper cites On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning.

Algorithmic Fairness: A Runtime Perspective On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning

Reference 23

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This paper cites In: Proceedings of the International Computer Aided Verification (CAV).

Algorithmic Fairness: A Runtime Perspective In: Proceedings of the International Computer Aided Verification (CAV)

Reference 24

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Observation 66bb9871-4f24-4e97-b5ce-0fe478b1d84e · outbound

This paper cites In: Proceedings of the ACM Conference on Fairness, Accountability, and Transparency (FAccT).

Algorithmic Fairness: A Runtime Perspective In: Proceedings of the ACM Conference on Fairness, Accountability, and Transparency (FAccT)

Reference 25

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Algorithmic Fairness: A Runtime Perspective Unresolved cited work

Reference 26

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Observation 5173cf69-41ca-4c57-9cfc-4f88f042ddd0 · outbound

This paper cites In: International Conference on Runtime Verification (RV).

Algorithmic Fairness: A Runtime Perspective In: International Conference on Runtime Verification (RV)

Reference 27

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Algorithmic Fairness: A Runtime Perspective Unresolved cited work

Reference 28

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Observation f7f3cf68-a635-4043-89d4-e7671a452b6c · outbound

This paper cites Journal of the American Statistical Association58(301), 13–30 (1963).

Algorithmic Fairness: A Runtime Perspective Journal of the American Statistical Association58(301), 13–30 (1963)

Reference 29

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Algorithmic Fairness: A Runtime Perspective The Annals of Statistics49(2), 1055–1080 (2021)

Reference 30

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This paper cites In: International Conference on Machine Learning.

Algorithmic Fairness: A Runtime Perspective In: International Conference on Machine Learning

Reference 31

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Algorithmic Fairness: A Runtime Perspective In: Conference on Uncertainty in Artificial Intelligence

Reference 32

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Algorithmic Fairness: A Runtime Perspective In: International Conference on Computer Aided Verification

Reference 33

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Algorithmic Fairness: A Runtime Perspective In: International Conference on Machine Learning

Reference 34

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Algorithmic Fairness: A Runtime Perspective Journal of Machine Learning Research23 (2022)

Reference 35

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This paper cites Advances in neural information processing systems30 (2017).

Algorithmic Fairness: A Runtime Perspective Advances in neural information processing systems30 (2017)

Reference 36

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Algorithmic Fairness: A Runtime Perspective In: International Conference on Machine Learning

Reference 37

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Observation 040f43dd-88d5-42ec-8229-c35c95d860a5 · outbound

This paper cites In: International Symposium on Formal Techniques in Real-Time and Fault-Tolerant Systems.

Algorithmic Fairness: A Runtime Perspective In: International Symposium on Formal Techniques in Real-Time and Fault-Tolerant Systems

Reference 38

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This paper cites ACM Computing Surveys (CSUR)54(6), 1–35 (2021).

Algorithmic Fairness: A Runtime Perspective ACM Computing Surveys (CSUR)54(6), 1–35 (2021)

Reference 39

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This paper cites Advances in Neural Information Processing Systems (NeurIPS) 34, 26276–26288 (2021).

Algorithmic Fairness: A Runtime Perspective Advances in Neural Information Processing Systems (NeurIPS) 34, 26276–26288 (2021)

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:26:54.232408Z

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Observation 8c4e7bbe-2141-4e9a-b635-f865585d4675 · outbound

This paper cites Cambridge Series in Statistical and Probabilistic Mathematics, Cambridge University Press (1997).

Algorithmic Fairness: A Runtime Perspective Cambridge Series in Statistical and Probabilistic Mathematics, Cambridge University Press (1997)

Reference 41

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This paper cites Science366(6464), 447–453 (2019).

Algorithmic Fairness: A Runtime Perspective Science366(6464), 447–453 (2019)

Reference 42

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Algorithmic Fairness: A Runtime Perspective Proceed- ings of the ACM on Human-Computer Interaction3(CSCW), 1–33 (2019)

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:26:54.169953Z

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This paper cites Advances in Neural Information Process- ing Systems 32 (2019).

Algorithmic Fairness: A Runtime Perspective Advances in Neural Information Process- ing Systems 32 (2019)

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:26:54.146523Z

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This paper cites In: International conference on runtime verification.

Algorithmic Fairness: A Runtime Perspective In: International conference on runtime verification

Reference 45

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This paper cites In: International Symposium on Formal Methods.

Algorithmic Fairness: A Runtime Perspective In: International Symposium on Formal Methods

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:26:54.108086Z

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This paper cites IEEE transac- tions on visualization and computer graphics26(1), 56–65 (2019).

Algorithmic Fairness: A Runtime Perspective IEEE transac- tions on visualization and computer graphics26(1), 56–65 (2019)

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:26:54.086832Z

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This paper cites In: International conference on machine learning.

Algorithmic Fairness: A Runtime Perspective In: International conference on machine learning

Reference 48

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Observation 9cacee22-4611-46d6-90b7-bd4d7d0d85d6 · outbound

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Algorithmic Fairness: A Runtime Perspective Unresolved cited work

Reference 3158

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Pith citing papers

No inbound Pith citation observations are available.