Fairness Testing through Extreme Value Theory | Paper Citation Record

Observation f867f712-fc9e-4df6-bf74-dca5e6f389df · outbound

This paper cites Goodfellow, Y.

Fairness Testing through Extreme Value Theory Goodfellow, Y

Reference 1

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Observation f17c3098-8537-48d2-a587-45dc3b431dd0 · outbound

This paper cites an unresolved cited work.

Fairness Testing through Extreme Value Theory Unresolved cited work

Reference 2

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Observation c0203f34-fd76-4860-a2cb-c07b24e4f02d · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Fairness Testing through Extreme Value Theory BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 3

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Observation a0c5ae76-ed3c-446c-86c5-56e3d053e8aa · outbound

This paper cites Chatgpt: Optimizing language models for dialogue,.

Fairness Testing through Extreme Value Theory Chatgpt: Optimizing language models for dialogue,

Reference 4

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Observation c41484ed-5b40-4964-b489-f63c309953bc · outbound

This paper cites Machine bias,.

Fairness Testing through Extreme Value Theory Machine bias,

Reference 5

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Observation 33d79e4d-00ff-4e6b-8b87-9633ba45134b · outbound

This paper cites ” computer says no!.

Fairness Testing through Extreme Value Theory ” computer says no!

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.274686Z

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Observation b86dc3fe-13b8-459b-8f41-06d37045350f · outbound

This paper cites Automated government for vulnerable citizens: Intermediating rights,.

Fairness Testing through Extreme Value Theory Automated government for vulnerable citizens: Intermediating rights,

Reference 7

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Observation fe858fb8-1f99-474b-a045-c9faf676f737 · outbound

This paper cites The IRS is targeting the poorest americans,.

Fairness Testing through Extreme Value Theory The IRS is targeting the poorest americans,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.241172Z

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Observation 3bff96c8-ca29-4182-aa2f-4a0cbe8e7fb6 · outbound

This paper cites Metamorphic testing and debugging of tax preparation soft- ware,.

Fairness Testing through Extreme Value Theory Metamorphic testing and debugging of tax preparation soft- ware,

Reference 9

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Observation 5b85654c-0722-4de6-b6c1-3dba8b35ac4e · outbound

This paper cites The gender gap in employment and wages,.

Fairness Testing through Extreme Value Theory The gender gap in employment and wages,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.214796Z

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Observation 914d3f52-0b59-4dbb-b404-e81b511be350 · outbound

This paper cites Racial differences in access to high- paying jobs and the wage gap between black and white women,.

Fairness Testing through Extreme Value Theory Racial differences in access to high- paying jobs and the wage gap between black and white women,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.201321Z

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Observation e41beead-cab4-4ed5-a17e-c097489ed4fa · outbound

This paper cites Fairness through awareness,.

Fairness Testing through Extreme Value Theory Fairness through awareness,

Reference 12

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Observation 217a6f03-f856-44dd-94d7-f3b0987834e7 · outbound

This paper cites Coles, J.

Fairness Testing through Extreme Value Theory Coles, J

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.180139Z

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Observation 5078f0c0-e61a-4b06-a979-34173cd263a6 · outbound

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

Fairness Testing through Extreme Value Theory Fairness testing: testing software for discrimination,

Reference 14

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Observation a481e81c-526b-4512-93f7-0b34a201dcfa · outbound

This paper cites Fairness risk measures,.

Fairness Testing through Extreme Value Theory Fairness risk measures,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.166367Z

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Observation cc1a61fe-43f3-4262-8bda-70ac620f096e · outbound

This paper cites A goodness-of-fit test for the distribution tail,.

Fairness Testing through Extreme Value Theory A goodness-of-fit test for the distribution tail,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.150631Z

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Observation 8dd03e8a-cc9c-4648-98dc-6a29a36910e8 · outbound

This paper cites Measurement- based worst-case execution time estimation using the coefficient of variation,.

Fairness Testing through Extreme Value Theory Measurement- based worst-case execution time estimation using the coefficient of variation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.135064Z

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Observation 42b01a62-6fed-4b93-866d-d08d597a370a · outbound

This paper cites an unresolved cited work.

Fairness Testing through Extreme Value Theory Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-10T18:10:16.120409Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dfd9eeee-56ac-461a-b414-bd968aed8fe5 · outbound

This paper cites Variational autoencoder based synthetic data generation for imbalanced learning,.

Fairness Testing through Extreme Value Theory Variational autoencoder based synthetic data generation for imbalanced learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.104509Z

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Observation 155c8088-df0c-49ea-9842-ae4b45e01314 · outbound

This paper cites A reductions approach to fair classification,.

Fairness Testing through Extreme Value Theory A reductions approach to fair classification,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.088990Z

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Observation a3546523-3126-4e3e-87b9-90d77af8a060 · outbound

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

Fairness Testing through Extreme Value Theory Bias in machine learning software: Why? how? what to do?

Reference 21

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Observation 25406fdf-9bd4-4450-acb6-2d0645d8fe46 · outbound

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

Fairness Testing through Extreme Value Theory Maat: a novel ensemble approach to addressing fairness and performance bugs for machine learning software,

Reference 22

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Observation 597ebf3d-7db9-4d4f-aac4-b37724aa81cc · outbound

This paper cites Don’t lie to me: Avoiding malicious explanations with stealth,.

Fairness Testing through Extreme Value Theory Don’t lie to me: Avoiding malicious explanations with stealth,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.075621Z

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Observation 0373a5a0-4bc4-4d21-8831-a73439c2a1bf · outbound

This paper cites Minimax group fairness: Algorithms and experiments,.

Fairness Testing through Extreme Value Theory Minimax group fairness: Algorithms and experiments,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T18:10:14.044286Z

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Observation dd56de61-57f3-48bd-8458-b8304deb4e29 · outbound

This paper cites an unresolved cited work.

Fairness Testing through Extreme Value Theory Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-10T18:10:16.062088Z

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Observation fe61bb52-2a2e-486d-9d0b-96f4e1588da0 · outbound

This paper cites UCI machine learning repository,.

Fairness Testing through Extreme Value Theory UCI machine learning repository,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.046122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1b28a2fd-2d7f-41a0-893d-8f7e386b2f19 · outbound

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

Fairness Testing through Extreme Value Theory White-box fairness testing through adversarial sampling,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.031040Z

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Observation 7e7745ba-b3ed-42f2-a204-56cbfde41058 · outbound

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

Fairness Testing through Extreme Value Theory Neuronfair: Interpretable white-box fairness testing through biased neuron identification,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.016806Z

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Observation 03106166-6047-4c48-893d-b3ee2eec8f52 · outbound

This paper cites Efficient white-box fairness testing through gradient search,.

Fairness Testing through Extreme Value Theory Efficient white-box fairness testing through gradient search,

Reference 29

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Observation 94acd4cc-a9ed-45cf-aee0-4d981e497450 · outbound

This paper cites UCI:heart disease data set,.

Fairness Testing through Extreme Value Theory UCI:heart disease data set,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:16.002241Z

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Observation 8179cae1-21aa-4a05-b112-e7171c70b802 · outbound

This paper cites Automated directed fairness testing,.

Fairness Testing through Extreme Value Theory Automated directed fairness testing,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T18:10:14.079178Z

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Observation a567bc50-7256-4741-8459-e184ebf52578 · outbound

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

Fairness Testing through Extreme Value Theory Neuronfair: interpretable white-box fairness testing through biased neuron identification,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T18:10:14.084149Z

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Observation db6b7173-3172-4211-b2f7-be0d33514eb0 · outbound

This paper cites Ctab-gan: Effective table data synthesizing,.

Fairness Testing through Extreme Value Theory Ctab-gan: Effective table data synthesizing,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.987818Z

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Observation bfcca2c2-e4a4-4f75-a4d8-60e3b9a372ff · outbound

This paper cites Autogan: An automated human-out-of-the-loop approach for training generative adversarial networks,.

Fairness Testing through Extreme Value Theory Autogan: An automated human-out-of-the-loop approach for training generative adversarial networks,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.956675Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0b76a153-55bb-4060-849c-d6cccefeb4de · outbound

This paper cites Distance correlation gan: Fair tabular data generation with generative adversarial networks,.

Fairness Testing through Extreme Value Theory Distance correlation gan: Fair tabular data generation with generative adversarial networks,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T18:10:14.102488Z

Source-reported events for the cited work

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Observation f2647a5f-8914-4b93-a4b7-d8fec97cdbfd · outbound

This paper cites Learning Classifiers from Synthetic Data Using a Multichannel Autoencoder.

Fairness Testing through Extreme Value Theory Learning Classifiers from Synthetic Data Using a Multichannel Autoencoder

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-10T18:10:14.651233Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4f333612-89db-48a9-9877-28c5051718a4 · outbound

This paper cites Crash data augmentation using variational autoencoder,.

Fairness Testing through Extreme Value Theory Crash data augmentation using variational autoencoder,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.943150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d80f63ae-71f5-4e2b-835a-907f0b87159d · outbound

This paper cites Latent imitator: Generating natural individual discriminatory instances for black-box fairness testing,.

Fairness Testing through Extreme Value Theory Latent imitator: Generating natural individual discriminatory instances for black-box fairness testing,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.929535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3f90d512-b9a3-48f7-93c1-d3d6c411e70c · outbound

This paper cites Methods to distinguish between polynomial and exponential tails,.

Fairness Testing through Extreme Value Theory Methods to distinguish between polynomial and exponential tails,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.913984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2ecd5eca-1637-454c-931e-ca39a26cb4bd · outbound

This paper cites Biometry: The principles and practice of statistics in biological research 3rd edition wh freeman and co,.

Fairness Testing through Extreme Value Theory Biometry: The principles and practice of statistics in biological research 3rd edition wh freeman and co,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.898085Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4ab95869-9f3d-4101-87df-efa58d430a82 · outbound

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

Fairness Testing through Extreme Value Theory Fairness-aware configuration of machine learning libraries,

Reference 42

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Source-reported events for the cited work

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Observation a57ac15a-c041-408d-92f3-ee17ffbb9547 · outbound

This paper cites Fairlearn: A toolkit for assessing and improving fairness in AI,.

Fairness Testing through Extreme Value Theory Fairlearn: A toolkit for assessing and improving fairness in AI,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.874429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f961b1fd-f46f-4c08-ae34-ab3531989e59 · outbound

This paper cites UCI machine learning repository (german credit),.

Fairness Testing through Extreme Value Theory UCI machine learning repository (german credit),

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.858796Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 99252bb6-b005-40ae-9e29-e35ee194a49f · outbound

This paper cites UCI machine learning repository (bank marketing),.

Fairness Testing through Extreme Value Theory UCI machine learning repository (bank marketing),

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.843569Z

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Observation 6cd97146-1508-41bb-a0c1-c07a35a73111 · outbound

This paper cites Compas software ananlysis,.

Fairness Testing through Extreme Value Theory Compas software ananlysis,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.828173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5c8ff8b4-16bf-49ae-862c-5b64f00fa292 · outbound

This paper cites UCI:default of credit card clients data set,.

Fairness Testing through Extreme Value Theory UCI:default of credit card clients data set,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.813113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation afea3d40-6305-4323-b29d-e38d890acea7 · outbound

This paper cites Medical expenditure panel survey,.

Fairness Testing through Extreme Value Theory Medical expenditure panel survey,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.795798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6f0688ae-68a9-4bb8-b1e3-972537e4c5cb · outbound

This paper cites Student performance data set,.

Fairness Testing through Extreme Value Theory Student performance data set,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.646036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b3eec0bf-0579-4a40-a085-88844e56f24a · outbound

This paper cites TensorFlow: Large-scale machine learning on heterogeneous systems,.

Fairness Testing through Extreme Value Theory TensorFlow: Large-scale machine learning on heterogeneous systems,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.630849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f9f43adf-b72b-4baa-9f74-4dbcac145a00 · outbound

This paper cites Scikit-learn: Machine learning in Python,.

Fairness Testing through Extreme Value Theory Scikit-learn: Machine learning in Python,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T18:10:14.170396Z

Source-reported events for the cited work

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Observation 17ca5119-d21c-4260-9999-2aa5fd8cfed3 · outbound

This paper cites Automated directed fairness testing,.

Fairness Testing through Extreme Value Theory Automated directed fairness testing,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.604161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 706464c3-c866-4181-8046-c2ee1749578d · outbound

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

Fairness Testing through Extreme Value Theory Fairway: a way to build fair ml software,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.588381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 22a01795-bc34-444e-8d2d-19e07ab65496 · outbound

This paper cites Ai fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias,.

Fairness Testing through Extreme Value Theory Ai fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.575698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b2c9bdc9-ac49-47f3-a5b0-269c4fbac212 · outbound

This paper cites A software review for extreme value analysis,.

Fairness Testing through Extreme Value Theory A software review for extreme value analysis,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.560988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fd03b0ca-8cd3-4230-b1bf-e4129ded0ad5 · outbound

This paper cites Robust confidence intervals for effect sizes: A comparative study of cohen’s d and cliff’s delta under non-normality and heterogeneous variances,.

Fairness Testing through Extreme Value Theory Robust confidence intervals for effect sizes: A comparative study of cohen’s d and cliff’s delta under non-normality and heterogeneous variances,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.545734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c29f9e29-f5ca-4472-b642-e8cece91f89b · outbound

This paper cites Ranking and clustering software cost estimation models through a multiple comparisons algorithm,.

Fairness Testing through Extreme Value Theory Ranking and clustering software cost estimation models through a multiple comparisons algorithm,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.527666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b8828ff1-650a-4df7-b2cb-0cb36d00b552 · outbound

This paper cites Grouped correlational generative adversarial networks for discrete electronic health records,.

Fairness Testing through Extreme Value Theory Grouped correlational generative adversarial networks for discrete electronic health records,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.510276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 46a47a41-fbab-413b-afbe-7e3f2434b574 · outbound

This paper cites A note on the evaluation of generative models.

Fairness Testing through Extreme Value Theory A note on the evaluation of generative models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T18:10:14.209018Z

Source-reported events for the cited work

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Observation 0f751976-4234-4644-a1e3-d84c732eadc2 · outbound

This paper cites TabSynDex: A Universal Metric for Robust Evaluation of Synthetic Tabular Data.

Fairness Testing through Extreme Value Theory TabSynDex: A Universal Metric for Robust Evaluation of Synthetic Tabular Data

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-10T18:10:14.213602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a871a31-b20d-4a76-bb46-09eb60ba1094 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium,.

Fairness Testing through Extreme Value Theory Gans trained by a two time-scale update rule converge to a local nash equilibrium,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.494083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5af442f4-c089-4632-a339-cb2ad5c57373 · outbound

This paper cites The synthetic data vault,.

Fairness Testing through Extreme Value Theory The synthetic data vault,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.477231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 513d31d5-3a11-40d9-b9bb-f4dc0734a83c · outbound

This paper cites Borg and P.

Fairness Testing through Extreme Value Theory Borg and P

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.460012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1f1276ec-d121-4cb4-a6a0-668ca299c92b · outbound

This paper cites Automated Test Generation to Detect Individual Discrimination in AI Models.

Fairness Testing through Extreme Value Theory Automated Test Generation to Detect Individual Discrimination in AI Models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T18:10:14.231169Z

Source-reported events for the cited work

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Observation 2ee7893e-cc47-4c89-9d11-061bf9837715 · outbound

This paper cites Neufair: Neural network fairness repair with dropout,.

Fairness Testing through Extreme Value Theory Neufair: Neural network fairness repair with dropout,

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-10T18:10:14.235873Z

Source-reported events for the cited work

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Observation 32eacf49-14e2-466b-83b5-fb5b3d98526e · outbound

This paper cites Adaptive sam- pling for minimax fair classification,.

Fairness Testing through Extreme Value Theory Adaptive sam- pling for minimax fair classification,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.437458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7676cd7c-5b13-402c-a116-f78f5e7c8930 · outbound

This paper cites Characterizing intersectional group fairness with worst-case comparisons,.

Fairness Testing through Extreme Value Theory Characterizing intersectional group fairness with worst-case comparisons,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.418563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a1531099-78eb-41a9-acf6-3a9beaf88d88 · outbound

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

Fairness Testing through Extreme Value Theory Adaptive fairness improvement based on causality analysis,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.398839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a0630689-4b23-4c6e-a9df-9e978dfa57a4 · outbound

This paper cites Fairness improvement with multiple protected attributes: How far are we?.

Fairness Testing through Extreme Value Theory Fairness improvement with multiple protected attributes: How far are we?

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-10T18:10:14.254683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d785cf2c-6f69-40ae-a276-392a8776c6e5 · outbound

This paper cites Worst-case convergence time of ml algorithms via extreme value theory,.

Fairness Testing through Extreme Value Theory Worst-case convergence time of ml algorithms via extreme value theory,

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-10T18:10:14.260366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ad9113a-0046-48de-84f4-a68ef543501e · outbound

This paper cites Income inequality in the united states, 1913– 1998,.

Fairness Testing through Extreme Value Theory Income inequality in the united states, 1913– 1998,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.371220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 46e08353-c25c-4a90-acf5-98b979f0f09a · outbound

This paper cites Income and wealth concentration in a historical and interna- tional perspective, uc berkeley and nber, forthcoming in john quigley,.

Fairness Testing through Extreme Value Theory Income and wealth concentration in a historical and interna- tional perspective, uc berkeley and nber, forthcoming in john quigley,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.353349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7a30dc8c-c212-4449-8e90-e4d4eaa7985c · outbound

This paper cites Income Inequality in OECD Countries: Data and Explanations,.

Fairness Testing through Extreme Value Theory Income Inequality in OECD Countries: Data and Explanations,

Reference 73

Resolution: verified exact; doi, observed 2026-08-10T18:10:14.325453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3a21bf7a-bfaf-4c00-9efc-8e8a64a6f1eb · outbound

This paper cites Fairness metrics for recommender systems,.

Fairness Testing through Extreme Value Theory Fairness metrics for recommender systems,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:10:15.337050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7bdb6036-8294-4e2f-9848-e17c6131599f · outbound

This paper cites an unresolved cited work.

Fairness Testing through Extreme Value Theory Unresolved cited work

Reference 157

Resolution: unresolved; raw_fallback, observed 2026-08-10T18:10:15.973324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers