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Paper Citation Record · LEDGER

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems

As of 11 August 2026, this Paper Citation Record lists 100 of 107 outbound references and 1 inbound Pith citation observation for arXiv:2501.01665.

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

pith.paper-citation-record.v1
2501.01665 v1

Coverage vector

measured 100 of 107 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:27:32.079970Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:49:21.432618Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T19:49:23.039805Z

Reference resolution

100 of 107 outbound references displayed

  • verified exact2
  • verified fuzzy61
  • unresolved37
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 31526bc4-c09b-4ff5-a5b7-5b4939093e00 · outbound

This paper cites System Safety Engineering for Social and Ethical ML Risks: A Case Study.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems System Safety Engineering for Social and Ethical ML Risks: A Case Study

Reference 1

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Observation 5136b146-89c7-45b4-9f74-4eb34bd19e23 · outbound

This paper cites Delayed impact of fair machine learning,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Delayed impact of fair machine learning,

Reference 2

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source=pdf_text observed=2026-08-10T22:27:31.700604Z digest=sha256:bce434eb03bae7010e55cd1910e30acc7b1148efaef04349ad0d091a9a294a56

Observation aff63afd-ff55-476b-abbd-0ed390870bb9 · outbound

This paper cites Runaway feedback loops in predictive policing,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Runaway feedback loops in predictive policing,

Reference 3

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source=pdf_text observed=2026-08-10T22:27:31.704830Z digest=sha256:c8f2c4cf71b0c04266bdb0d70f589481447731ce20db59d1ffc9438543f40d6a

Observation 7bde42c0-e379-41bf-a305-0bc519246ccf · outbound

This paper cites On adaptive fairness in software systems,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems On adaptive fairness in software systems,

Reference 4

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Observation 5973acdd-fa9f-4c3d-a73e-33afa710e535 · outbound

This paper cites Fairness testing: testing software for discrimination,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairness testing: testing software for discrimination,

Reference 5

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source=pdf_text observed=2026-08-10T22:27:31.712819Z digest=sha256:82550f2a8ee48a039a88027ca100114c959338c6a82c723c4ebae7ad1ecfa962

Observation 292f0387-59a9-49ef-8a21-88b0cabc6502 · outbound

This paper cites Do the machine learning models on a crowd sourced platform exhibit bias? an empirical study on model fairness,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Do the machine learning models on a crowd sourced platform exhibit bias? an empirical study on model fairness,

Reference 6

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source=pdf_text observed=2026-08-10T22:27:31.716883Z digest=sha256:4f33d5e1940bc020e067e8685c61c5413acd90a2de38fdb1b30d5256fc2ce7de

Observation 1855fb73-bbbc-41be-8f22-769fbdd11ba2 · outbound

This paper cites Fair preprocessing: Towards understanding compositional fairness of data transformers in machine learning pipeline,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fair preprocessing: Towards understanding compositional fairness of data transformers in machine learning pipeline,

Reference 7

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source=pdf_text observed=2026-08-10T22:27:31.720996Z digest=sha256:6b990b2bf819468e0ddbc347d36143c037b3f27a3813bc1b9efb0a9ec2eb6128

Observation 8d9b28d7-9da0-4721-a305-09c925526848 · outbound

This paper cites Black box fairness testing of machine learning models,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Black box fairness testing of machine learning models,

Reference 8

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Observation a5f23421-ef3f-4d6a-9cd8-13d2bd8757b6 · outbound

This paper cites Automated directed fairness testing,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Automated directed fairness testing,

Reference 9

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source=pdf_text observed=2026-08-10T22:27:31.729079Z digest=sha256:cc54ff5bd6e4fa0ff43239c5fa8c400641873895045833cf7173dd32adb5279d

Observation 7cb1bc08-a832-4f11-a4e2-fa49ad5bdd1f · outbound

This paper cites White-box fairness testing through adversarial sampling,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems White-box fairness testing through adversarial sampling,

Reference 10

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source=pdf_text observed=2026-08-10T22:27:31.732550Z digest=sha256:ab3e2eeb927e8438cfc88403b33abf38bf69f200b338bdd125319bfff8d984f7

Observation a5f99e7c-35e1-48ce-9164-5a62f1b9147a · outbound

This paper cites Fairify: Fairness verification of neural networks,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairify: Fairness verification of neural networks,

Reference 11

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source=pdf_text observed=2026-08-10T22:27:31.736284Z digest=sha256:e0094d0bfd0c058f8a92749df72716958d8440a3a5a27d414b91e6ce29c4aad0

Observation 81954c3b-2574-4f0c-b62f-079f1c338f2b · outbound

This paper cites Bias in machine learning software: Why? how? what to do?.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Bias in machine learning software: Why? how? what to do?

Reference 12

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source=pdf_text observed=2026-08-10T22:27:31.740049Z digest=sha256:3d033915a24c383aa095a67eaf22b315e2e3b0e0f06c5b900d62496c97dbb025

Observation d3563a86-61a7-4c79-9eaf-45d696cf8699 · outbound

This paper cites Fairway: A way to build fair ml software,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairway: A way to build fair ml software,

Reference 13

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Observation 4d13c222-cd65-4af9-a897-4cc7e4d7103c · outbound

This paper cites Fix fairness, don’t ruin accuracy: Performance aware fairness repair using automl,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fix fairness, don’t ruin accuracy: Performance aware fairness repair using automl,

Reference 14

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Observation 55a2d31b-1635-4764-ba61-88db567d4377 · outbound

This paper cites an unresolved cited work.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Unresolved cited work

Reference 15

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Observation 351102fc-652c-4d2c-9df3-ded3e46f9e02 · outbound

This paper cites an unresolved cited work.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Unresolved cited work

Reference 16

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source=pdf_text observed=2026-08-10T22:27:31.756243Z digest=sha256:96cc42410bf38198d4d2956f52de8f0cd076bc5225fb9ec257b5f7d74b264fce

Observation dd925a31-eddd-4135-9eeb-e1ec4c836f01 · outbound

This paper cites O’Neil, Weapons of math destruction: How big data increases inequality and threatens democracy.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems O’Neil, Weapons of math destruction: How big data increases inequality and threatens democracy

Reference 17

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Observation cf3288a8-496f-40f7-bb4a-f50648bacdf1 · outbound

This paper cites Concrete problems in ai safety,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Concrete problems in ai safety,

Reference 18

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source=pdf_text observed=2026-08-10T22:27:31.762630Z digest=sha256:0bbec58913e81f9ee2a2a3c8fb166143432dbc7260e27d5c47ab54c75b5a45ee

Observation 553555ba-68d5-4a2b-897b-63060ae17fb3 · outbound

This paper cites Fairness is not static: deeper understanding of long term fairness via simulation studies,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairness is not static: deeper understanding of long term fairness via simulation studies,

Reference 19

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Observation 8393bc43-bc96-4d90-9cd4-0a0f034e8889 · outbound

This paper cites Runtime monitoring of dynamic fairness properties,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Runtime monitoring of dynamic fairness properties,

Reference 20

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source=pdf_text observed=2026-08-10T22:27:31.770350Z digest=sha256:3960b2af777b8ece507806b61671e7c95e2275a415bd9b678f5f6e82bc7af872

Observation 83c70a9d-e3ae-484e-a813-999c175135a6 · outbound

This paper cites Extending the Machine Learning Abstraction Boundary: A Complex Systems Approach to Incorporate Societal Context.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Extending the Machine Learning Abstraction Boundary: A Complex Systems Approach to Incorporate Societal Context

Reference 21

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Observation 17ada676-d7d0-4bc7-b05b-2499bae54462 · outbound

This paper cites A classification of feedback loops and their relation to biases in automated decision-making systems,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems A classification of feedback loops and their relation to biases in automated decision-making systems,

Reference 22

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Observation 5e7c5dc3-8311-48b3-ad69-e79b98eba0e1 · outbound

This paper cites Towards safe ML-based systems in presence of feedback loops,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Towards safe ML-based systems in presence of feedback loops,

Reference 23

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Observation f33600ea-2296-4b4a-8bbb-8e09fdeb1439 · outbound

This paper cites The world and the machine,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems The world and the machine,

Reference 24

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Observation a54b2b7b-8699-490c-8729-a3a43bde8ca1 · outbound

This paper cites A reference model for requirements and specifications,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems A reference model for requirements and specifications,

Reference 25

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source=pdf_text observed=2026-08-10T22:27:31.790331Z digest=sha256:6dca1a17f8988bd1be5cf0696841f2f0bbcc082633630d61a654e819b4eee0ec

Observation 846cdaa2-ed52-4a4c-9375-c0c0a70215a2 · outbound

This paper cites an unresolved cited work.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Unresolved cited work

Reference 26

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Observation 0af2144f-af40-476a-a437-b14abb7b9288 · outbound

This paper cites Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models,

Reference 27

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Observation cac90c26-b9a6-4dee-acbe-1bad0a8e87b6 · outbound

This paper cites Algorithmic fairness in predicting opioid use disorder using machine learning,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Algorithmic fairness in predicting opioid use disorder using machine learning,

Reference 28

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Observation 7e63a085-f40f-4e76-83f0-b8f0a797e56f · outbound

This paper cites The effect of differential victim crime reporting on predictive policing systems,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems The effect of differential victim crime reporting on predictive policing systems,

Reference 29

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Observation 815725d1-d48a-4ae5-bb29-df276d120612 · outbound

This paper cites The role of environmental deviations in engineering robust systems,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems The role of environmental deviations in engineering robust systems,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 8afcc1b9-675c-4b04-a62e-4a1acd73b1ae · outbound

This paper cites Fairness definitions explained,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairness definitions explained,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 04102ae8-5917-49b2-a38e-141c9a72d5f1 · outbound

This paper cites Fairness through awareness,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairness through awareness,

Reference 32

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Observation 62ccff9d-1f2e-45b8-92a4-63ccbdba86e3 · outbound

This paper cites Equality of opportunity in supervised learning,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Equality of opportunity in supervised learning,

Reference 33

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Source-reported events for the cited work

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Observation 84eb32f2-80e9-44a1-bf52-d1f7ebd8f961 · outbound

This paper cites Artificial intolerance,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Artificial intolerance,

Reference 34

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source=pdf_text observed=2026-08-10T22:27:31.825374Z digest=sha256:0b57b5ecbfcfc514727cd8b26dc6d04acabfc77d52dc8b61a995530bdca58470

Observation 756b34e9-c860-46b0-b658-9dff9f0bf8aa · outbound

This paper cites Black Loans Matter: Distributionally Robust Fairness for Fighting Subgroup Discrimination.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Black Loans Matter: Distributionally Robust Fairness for Fighting Subgroup Discrimination

Reference 35

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Observation 95cd1692-3310-4142-9bb5-1e352b66820d · outbound

This paper cites Justice department secures over 31 million from city national bank to address lending discrimination allegations,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Justice department secures over 31 million from city national bank to address lending discrimination allegations,

Reference 36

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source=pdf_text observed=2026-08-10T22:27:31.837452Z digest=sha256:ede02f49565aa50e733dca1010c82d63f6c4bb255d2ad14aa5da0ace1f07422e

Observation 63228970-2568-44ec-8c4b-d0ce2db0f0d4 · outbound

This paper cites Apple card is accused of gender bias. here’s how that can happen,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Apple card is accused of gender bias. here’s how that can happen,

Reference 37

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.841347Z digest=sha256:494a7edca9590092ef0cb1df0210295537e8bdb314ceaadc7e0bf89afaf59515

Observation 250b162e-8084-4cae-869b-ecc137d7dc84 · outbound

This paper cites Fairtest: Discovering unwarranted associa- tions in data-driven applications,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairtest: Discovering unwarranted associa- tions in data-driven applications,

Reference 38

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raw_fallback, observed 2026-08-10T22:27:32.991664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.844735Z digest=sha256:3cf66652ba2c6e9f619fe338268a1e3ec6a737596eda4371048dd2b14d86ade3

Observation c1375ec5-08ea-45c2-9104-d4dd698b1d57 · outbound

This paper cites an unresolved cited work.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:27:32.979702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.848851Z digest=sha256:0654365abcab55ba9911122970667b02dc591507202e4311eea4446238bdb825

Observation 88581db4-110b-49d3-b82b-c2817e66040a · outbound

This paper cites A brief survey of stopping rules in monte carlo simulations,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems A brief survey of stopping rules in monte carlo simulations,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.969404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.852180Z digest=sha256:9702b6f1a19271bf798963bd5dad640fb60ec53d6b7daf0651c5842e64b2a9dc

Observation b5fa3526-8556-4893-9129-cddaa2cfcb73 · outbound

This paper cites Saltelli, M.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Saltelli, M

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.959218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.855871Z digest=sha256:88657234f770998ef6d8321e3b282c60c1400eca1e4e8c0ab5b78779a4c45927

Observation d8e61523-48f8-4cd1-a193-d00ff785d868 · outbound

This paper cites Marrying fairness and explainability in supervised learning,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Marrying fairness and explainability in supervised learning,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.948513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.859547Z digest=sha256:b3550f340a1de0df71a791133aa869f1fdaedab447f99932a886d402ef1a7b40

Observation 0fe9c0ff-2250-4590-a47d-db5d7ac059b8 · outbound

This paper cites “how biased are your features?.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems “how biased are your features?

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.936949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.863208Z digest=sha256:bb16fd7d04d3bc2ae66c561d8138bc76d7b804262fc80933ac6f4986f2dc71bb

Observation 1773480a-4930-40ca-b847-b8d2fb5ec75a · outbound

This paper cites John Wiley & Sons, Ltd, 2007, ch.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems John Wiley & Sons, Ltd, 2007, ch

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.925276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.867162Z digest=sha256:fe11864cddf1316b435bc8e00335d252f7d4e6b73f5a730527d22d65916d3276

Observation d0ed8525-06e8-42ff-aaea-65b84b2ab4c5 · outbound

This paper cites John Wiley & Sons, Ltd, 2007.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems John Wiley & Sons, Ltd, 2007

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.913509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.871291Z digest=sha256:b8ef1c71a9f6cb9e6a47a4e8be2b3ca0031ff59b25024e6e70319e0c7c1821de

Observation d66450b1-87e7-4906-b0c6-cdad78dc0a71 · outbound

This paper cites Statistical methods for research workers,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Statistical methods for research workers,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.902052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.875374Z digest=sha256:e753a02b4831a39cf41e5e7b4812f91606303586494ae0f9b1d7680866d089d0

Observation b31ba5d0-8190-45c1-8721-9309b71f182a · outbound

This paper cites Cohen, P.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Cohen, P

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.890322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.879096Z digest=sha256:69c6bf10d9d55c2dc87d1965e4876eb9790178822fbe2f9972f66105469c7c9d

Observation 1a501909-7c40-42f3-8a57-a5d62af5c5b2 · outbound

This paper cites Hartman, Software and Hardware Testing Using Combinatorial Covering Suites.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Hartman, Software and Hardware Testing Using Combinatorial Covering Suites

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.877023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.882815Z digest=sha256:6c7dbc80d2300d8567a33a1f6e4f98fc3ca5e70312e2c79fc6b04071124fae8a

Observation 8830ff98-1012-4267-8ba0-8bd1264866a9 · outbound

This paper cites an unresolved cited work.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:27:32.865432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.886463Z digest=sha256:31c24e79d7939fa54a386ca1c7c8a1c13d6af37c574e68d08f7f6d8a5b51531a

Observation 7dbad8fc-75f2-4897-bd9c-5bf7aee0d456 · outbound

This paper cites an unresolved cited work.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:27:32.847947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.890630Z digest=sha256:cbd7a18a6206a2cf65e6cb095ac663a34be1b95d1ea1c3d0dedc715a4e61a071

Observation 830f7a1c-8701-4a54-be7a-c9a2bcfddfe1 · outbound

This paper cites Dosing discrimination: regulating pdmp risk scores,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Dosing discrimination: regulating pdmp risk scores,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.835444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.894267Z digest=sha256:0442902bd9da166b06f844941de538ada1b260703810a6f45a7ec98928dd7349

Observation 6be8845d-dae8-4ed7-a57b-8e548ac98686 · outbound

This paper cites Predictive modelling of susceptibility to substance abuse, mortality and drug-drug interactions in opioid patients,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Predictive modelling of susceptibility to substance abuse, mortality and drug-drug interactions in opioid patients,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.822799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.898093Z digest=sha256:84f30b521d0d327edb8117b84b01e347ba9b128cd523864f7adadb2b8c0aecaf

Observation 7b12b443-0ad9-4bc2-a092-725aabd69b75 · outbound

This paper cites Mimic-iv, a freely accessible electronic health record dataset,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Mimic-iv, a freely accessible electronic health record dataset,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.811043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.901568Z digest=sha256:fbcbba17a09cc3a7a11a726c4919542444532b700c6cdde793a099557be5174e

Observation 77697e85-e815-4406-b0b3-8798423181df · outbound

This paper cites Compstat and organizational change: A national assessment,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Compstat and organizational change: A national assessment,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.799816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.905700Z digest=sha256:b739fb1cd7a2ca0ef305922526b2661cf01e1dc1f261584523b04fe04c1550fd

Observation 60d5d801-31aa-44e4-88cf-3d03658899ed · outbound

This paper cites To predict and serve?.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems To predict and serve?

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.788392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.909244Z digest=sha256:f20bbe422d190c8a37de9214ad622cc8aa139451cf07f0baf6a24fe62e7e3080

Observation 5f7bbf1f-8b00-42c8-b271-01aff78e7c4c · outbound

This paper cites A similarity measure for indefinite rankings,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems A similarity measure for indefinite rankings,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.777030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.912796Z digest=sha256:01839213ee7690e6394f352951b80e42ddf0eed953701bf85cf45a086fa11502

Observation 73fd50d3-14b6-4219-b3c4-503fe93defe9 · outbound

This paper cites A new measure of rank correlation,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems A new measure of rank correlation,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.765025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.916589Z digest=sha256:3eb88d524a39f9570052d49c4e17f24f6d2af166b536393a2ab77928dc3a43db

Observation de5bdcdb-4f77-4c33-b9cf-58fd14a4abd4 · outbound

This paper cites Long-term fairness with unknown dynamics,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Long-term fairness with unknown dynamics,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.752897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.920453Z digest=sha256:274d5f0b28883957a0a0911da3b759e77d7be6573d263b8a57493ea90e2dacce

Observation 8275daf6-d3c5-4236-98a3-1b8f431f0b74 · outbound

This paper cites A call for better validation of opioid overdose risk algorithms,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems A call for better validation of opioid overdose risk algorithms,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.740453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.925143Z digest=sha256:feb1f3fdf123970bcc39c3257d8737c41a251cb903a9a4ed21cd89db78ba19c1

Observation 2dbfcf94-3824-4c21-9e25-d5019bd09d93 · outbound

This paper cites Hidden risks of machine learning applied to healthcare: unintended feed- back loops between models and future data causing model degradation,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Hidden risks of machine learning applied to healthcare: unintended feed- back loops between models and future data causing model degradation,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.727940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.928979Z digest=sha256:411b21988bd830f3bb9dd257452c54648f3a53f032bb76b87b0d5a43f8e26a10

Observation 96104d48-253b-423f-9466-f878d8d70553 · outbound

This paper cites A comparative study of fairness-enhancing interventions in machine learning,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems A comparative study of fairness-enhancing interventions in machine learning,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.713904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.932437Z digest=sha256:0affd4c53a7ced848bcc24aeb06773682e9b6afd8f1033150fae4c86c0c87521

Observation 557af9f3-44cf-4b4e-ab6a-c112681a9f01 · outbound

This paper cites Fairness-aware configuration of machine learning libraries,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairness-aware configuration of machine learning libraries,

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-10T22:27:31.936062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:27:31.936062Z digest=sha256:24132aba7ae712d931adc48bf13b6dc1629fae05ca5bf7273e7723b9efb02474

Observation fe4a64eb-ad28-496d-b93c-ea1bd27a2321 · outbound

This paper cites “ignorance and prejudice.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems “ignorance and prejudice

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.691068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.939830Z digest=sha256:7f96494b77fa44ba2038633bc6afc6eecff70e387498c8b80f8aa4f8cc88c18c

Observation 69427084-16e7-4190-9b0d-a9faf3b2da50 · outbound

This paper cites Fair enough: Searching for sufficient measures of fairness,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fair enough: Searching for sufficient measures of fairness,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.678726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.943940Z digest=sha256:5665d21ecb93626ef9f04af53047bb90999ffde32edbeeaf1c2dc15b1dcda5ab

Observation 1579aa59-e3e3-4876-936c-5cf614d83568 · outbound

This paper cites Learning fair representations,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Learning fair representations,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.666833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.947700Z digest=sha256:68bcb4535916aa169dc46d2aaaba887fa1ddd81f3910ced772dd7d922bae6c9e

Observation ffc078d3-a32d-45b4-86f0-468b7124346c · outbound

This paper cites Certifying and removing disparate impact,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Certifying and removing disparate impact,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.655793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.951400Z digest=sha256:599fc287a02920b80cd17bbc36d60467dc3db5e796af79efcaa219dcc0c871a1

Observation a284b49a-02ec-4b6b-96f1-8d273c18c1a7 · outbound

This paper cites Fairness constraints: Mechanisms for fair classification,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairness constraints: Mechanisms for fair classification,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.643344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.955335Z digest=sha256:f30c3d1d0e93f5f26eae9113dbc5c165238393939fa525537d64e6ed6329631d

Observation 657dd8bf-2e49-460f-92d9-15770ed60c07 · outbound

This paper cites Data preprocessing techniques for classifi- cation without discrimination,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Data preprocessing techniques for classifi- cation without discrimination,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.632608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.959139Z digest=sha256:46b26f6d0573df070b1d24d34af0049750e338d3a2f06deb8f2a74dc58679824

Observation c37808f6-6eb8-4a2f-827e-b439a7724720 · outbound

This paper cites Mitigating unwanted biases with adversarial learning,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Mitigating unwanted biases with adversarial learning,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.621769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.962928Z digest=sha256:d1d01cbed5d840da6fad443f7caae1955f23f4ce96601678208330989995b757

Observation b04e6a1e-bdb7-4c1f-9659-fdfba76ebda8 · outbound

This paper cites Fairness-aware classifier with prejudice remover regularizer,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairness-aware classifier with prejudice remover regularizer,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.609585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.966564Z digest=sha256:12e7bf2bbf146c4ce19cf9c9313e8beb20993daa24d1d63c8de0171077b9cd4a

Observation 26539e8e-018f-42cc-bb99-8ef84912300f · outbound

This paper cites Maat: a novel ensemble approach to addressing fairness and performance bugs for machine learning software,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Maat: a novel ensemble approach to addressing fairness and performance bugs for machine learning software,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.598877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.970273Z digest=sha256:7f347078b988e6aac5a0b7387aadf2d3597cae37209ca7b953a3ee47ef5d666a

Observation 8386566c-9026-44d0-9dca-044b72b2e449 · outbound

This paper cites Are my deep learning systems fair? an empirical study of fixed-seed training,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Are my deep learning systems fair? an empirical study of fixed-seed training,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.587761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.973898Z digest=sha256:fddf499d52e81cd4136fa043b49c549bd528969eb713c7565dcb2c344ce6cc2f

Observation 5afd56bc-2eb5-4a92-b6a7-42df7442cb45 · outbound

This paper cites Adaptive fairness improvement based on causality analysis,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Adaptive fairness improvement based on causality analysis,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.576637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.977354Z digest=sha256:dae9af4c8bc0a8ab8a0a9f355cc6d55ad059ef9ae872c8ca570fb19643782898

Observation a23c9554-b888-41ed-98c8-29866bd4b5bc · outbound

This paper cites Improving fairness in machine learning systems: What do industry practitioners need?.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Improving fairness in machine learning systems: What do industry practitioners need?

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.563411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.980860Z digest=sha256:f2e45ddc58f0eef2a0528982999b92fba4918e6d795ce0acc3838ae6a46184d4

Observation 014250fa-9972-40b3-b35d-ae17bbfc0532 · outbound

This paper cites Neuronfair: Interpretable white-box fairness testing through biased neuron identification,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Neuronfair: Interpretable white-box fairness testing through biased neuron identification,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.551327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.984121Z digest=sha256:0dfe2021479e8d7a7cc3048a039280a9dc80101fd93fe02e9446203e0efac09c

Observation 7147dd9e-f806-420c-a262-b3309693dec0 · outbound

This paper cites Explanation-guided fairness testing through genetic algorithm,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Explanation-guided fairness testing through genetic algorithm,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.538832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.987222Z digest=sha256:b1047df406a98359a6c7a821b0b6981dc9a8a07f262696ed60bdc924733bf9a5

Observation 94439828-48df-466c-84ea-7148f8ec2a14 · outbound

This paper cites Information- theoretic testing and debugging of fairness defects in deep neural networks,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Information- theoretic testing and debugging of fairness defects in deep neural networks,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.525717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.990270Z digest=sha256:b543a5f18b1c416411eab86658814092e6bc670d356a6995b3548b85ca221cad

Observation 6ea0b077-ae26-4c99-a169-b156ca3b7e6b · outbound

This paper cites Astraea: Grammar- based fairness testing,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Astraea: Grammar- based fairness testing,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.512695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.994029Z digest=sha256:fb764b925cd75d0a0e4564db3a819ff25f42eb71f24e5cbedf56c4b27cb0be91

Observation 5bdaaf46-61f5-4342-8e6e-887a2190f621 · outbound

This paper cites Fairsquare: probabilistic verification of program fairness,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairsquare: probabilistic verification of program fairness,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.500496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:31.997737Z digest=sha256:69e7af5f05f150f904c828f9a7efb436af3d3c1f11a2f33c207c2329b5e0fa4f

Observation 1814680b-bb23-4597-b1fb-195a13ad61a9 · outbound

This paper cites Probabilistic verification of fairness properties via concentration,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Probabilistic verification of fairness properties via concentration,

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.488624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.001101Z digest=sha256:c3eb2ecff1ec01eba70cea2aae28bd01a705a79597b8e5e970ef7d9082ff08f2

Observation 90c6c8a0-e94d-42dd-95ee-85ffcf994a93 · outbound

This paper cites Verifying individual fairness in machine learning models,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Verifying individual fairness in machine learning models,

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.476867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.004840Z digest=sha256:467ce780e001d3bb94fe832cd1a705d624fba13087edf26486cfaf971c53c800

Observation 48a6dfa3-bd46-48c1-b4a1-9755278392fa · outbound

This paper cites Certifying the fairness of knn in the presence of dataset bias,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Certifying the fairness of knn in the presence of dataset bias,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.465214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.008719Z digest=sha256:51cc95d6310f69ae452719b2a62c850fdeb3108c843493e2c8863266880de2cb

Observation c797cae2-fb6a-44ca-82ef-970292c897ae · outbound

This paper cites Fairea: A model behaviour mutation approach to benchmarking bias mitigation methods,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairea: A model behaviour mutation approach to benchmarking bias mitigation methods,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.453955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.012483Z digest=sha256:dc4ce3ea4a97792003b440130525f041bf43469042246e8050439fafa4dc2d75

Observation 60070e66-48c6-45fc-85ef-e4cbd3832042 · outbound

This paper cites Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-10T22:27:32.016230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:27:32.016230Z digest=sha256:eaf4eef03fd7f10d19dfe6b8312de8f71718ce59fdbfc349564041e0f813c0c3

Observation 0b5cfeb6-9c29-40c7-90ef-70b9ae8c661d · outbound

This paper cites Achieving long-term fairness in sequential decision making,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Achieving long-term fairness in sequential decision making,

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.442742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.020452Z digest=sha256:380252370182544f62f57a1dbc6918046cf63c9cedbaa5260a71befaa09a68a0

Observation 9c6c2698-b720-4147-ba79-791602339bd4 · outbound

This paper cites Algorithms for fairness in sequential decision making,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Algorithms for fairness in sequential decision making,

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.432042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.024639Z digest=sha256:537b23fa2b5955bccfa1afe5765ebce216b47b32bc81e903c9366b601f632b11

Observation 0f89eb85-b7ab-425a-81e1-1f7dcb9755c7 · outbound

This paper cites From fair decision making to social equality,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems From fair decision making to social equality,

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.421438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.028824Z digest=sha256:e62228f6c12f11e3e5d8db505a5084d638a75662e2d27ffa25c9acbecaa6bdd0

Observation edb1b6b2-b1e0-4bc6-b6c0-ee77fa8d4990 · outbound

This paper cites Fairness-aware programming,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairness-aware programming,

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.410507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.032579Z digest=sha256:c2337dd7f8200335bad2361077402367f07a830437fecdf41a8c96e9b5a9a787

Observation 7bf13669-ca9a-4b93-95fa-d49430c2fa64 · outbound

This paper cites Monitoring algorithmic fairness,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Monitoring algorithmic fairness,

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.399606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.036793Z digest=sha256:d9805d6cdf1476f4be6e0a2d52a1924fe05fad392e4b4fd6a91fb85f8f990f80

Observation 7381214c-7ddc-4f5f-86af-015c339fb26f · outbound

This paper cites Enforcing Delayed-Impact Fairness Guarantees.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Enforcing Delayed-Impact Fairness Guarantees

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-10T22:27:32.040789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:27:32.040789Z digest=sha256:445e93cb4d49da69c6f0436a091d01e2c256f229192ebc936fe8d65911516bb2

Observation 6d2e24bd-6a43-41a7-9068-3b4cbe872b77 · outbound

This paper cites Long-term Fairness For Real-time Decision Making: A Constrained Online Optimization Approach.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Long-term Fairness For Real-time Decision Making: A Constrained Online Optimization Approach

Reference 91

Resolution
verified exact
local_arxiv, observed 2026-08-10T22:27:32.152859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.045055Z digest=sha256:efa0390b8fecc3341f75ec9f514c200c8518d86f23f372f53caff45d46b0ff1e

Observation 9e4652ca-7fb9-4d4d-b45d-006cacdb9ab2 · outbound

This paper cites The long arc of fairness: Formalisations and ethical discourse,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems The long arc of fairness: Formalisations and ethical discourse,

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.388846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.049225Z digest=sha256:696a8a2ab66770ad0e1f9b35b4dbe1ab9320a2295036a03d4461f4d20bfd0abd

Observation 5be93b08-4101-4af6-8aa4-b8f4d07575b5 · outbound

This paper cites Fairness and abstraction in sociotechnical systems,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Fairness and abstraction in sociotechnical systems,

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.378226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.053322Z digest=sha256:e42b138046c1aa7642bc3ca746017b26ab7e7e2e61dc5bcbb540ea0abfef80c9

Observation 1b031471-5f3c-4d03-8dd4-3948da0b000b · outbound

This paper cites Requirements engineering for feedback loops in software-intensive systems,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Requirements engineering for feedback loops in software-intensive systems,

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.366665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.057317Z digest=sha256:19a299640fcb171bc1c84c8a5b4d2a87591e3f5a9d603980f47fc042b6f0be8d

Observation 69cd4083-12f7-4da4-b3ea-10e21e1f8b57 · outbound

This paper cites an unresolved cited work.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Unresolved cited work

Reference 95

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:27:32.355310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.061330Z digest=sha256:15e54ca5c1752cdb6c9259907a2a3ec047dd049b8525ac6ea296ac33b6c969cd

Observation 00b2b14b-f331-496b-a1a6-9ba7b386ae5e · outbound

This paper cites Data feedback loops: Model-driven amplification of dataset biases,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Data feedback loops: Model-driven amplification of dataset biases,

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.343141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.065074Z digest=sha256:af0b92ce422e24f72fc215652a2643fa968dfd55b3493c3a497f095036283ca4

Observation 5eead0f4-a600-4fd2-8e90-ae202d965c14 · outbound

This paper cites Hidden Incentives for Auto-Induced Distributional Shift.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Hidden Incentives for Auto-Induced Distributional Shift

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-10T22:27:32.068823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:27:32.068823Z digest=sha256:793971045fd627904c2417cacdc7b613ad6418871421bcd75037b318124a94b2

Observation faf5213b-f1d9-4c8a-86b7-1ce482ad3a27 · outbound

This paper cites Quinonero-Candela, M.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Quinonero-Candela, M

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.330947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.073012Z digest=sha256:588c5e26e292d8d15cc68b9e83bf2066f4c7ca048c562e83b96f7a9dc5f6e10f

Observation d93e73d6-8b72-423b-ac68-04c758a62047 · outbound

This paper cites Self-adaptation for machine learning based systems,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Self-adaptation for machine learning based systems,

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.318944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.076583Z digest=sha256:e288ef0b9ef748d52c64762db2d47c12644efda9cc6e40f1f8d16a65b2e6d23a

Observation 397928cc-7287-4c76-a595-8f1ba118e3b5 · outbound

This paper cites Models for understanding and quantifying feedback in societal systems,.

FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Models for understanding and quantifying feedback in societal systems,

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:27:32.304303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:27:32.079970Z digest=sha256:30fc2286c4e49c8f09b3c08ef3754aaa79eac4bee5b1783b09f0cfeaa7c195dd

Pith citing papers

Observation ef69133c-78b7-476c-a780-5779e944127d · inbound

Rethinking Autonomy: Preventing Failures in AI-Driven Software Engineering cites this paper.

Rethinking Autonomy: Preventing Failures in AI-Driven Software Engineering FairSense: Long-Term Fairness Analysis of ML-Enabled Systems

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-05T19:49:23.046973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:49:21.432618Z digest=sha256:ffe0eabe427ed8fb529f84f9e592675b3f68e5ffea8b678dd2f3354f103a558e