Exploring the Landscape of Fairness Interventions in Software Engineering | Paper Citation Record

Observation e0a02f48-4003-4dbd-841f-b23ef1b89eb4 · outbound

This paper cites https://deon.drivendata.org/.

Exploring the Landscape of Fairness Interventions in Software Engineering https://deon.drivendata.org/

Reference 1

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Observation e6e88a0a-61ef-4fd9-9edf-453119aafc3b · outbound

This paper cites https://ai.facebook.com/blog/ how-were-using-fairness-flow-to-help-build-ai-that-works-better-for-everyone/.

Exploring the Landscape of Fairness Interventions in Software Engineering https://ai.facebook.com/blog/ how-were-using-fairness-flow-to-help-build-ai-that-works-better-for-everyone/

Reference 2

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Observation 60c59692-3535-4b11-8122-9941182433c7 · outbound

This paper cites https://github.com/pymetrics/audit-ai./.

Exploring the Landscape of Fairness Interventions in Software Engineering https://github.com/pymetrics/audit-ai./

Reference 3

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Observation 45856e50-6597-4a8b-910f-f386b2384a33 · outbound

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Exploring the Landscape of Fairness Interventions in Software Engineering Unresolved cited work

Reference 4

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Observation 3253da62-0caf-42d3-9140-eb751ac8f67d · outbound

This paper cites an unresolved cited work.

Exploring the Landscape of Fairness Interventions in Software Engineering Unresolved cited work

Reference 5

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Observation 9bbaa696-29b0-4d5c-a9ab-07e3062c3eeb · outbound

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Exploring the Landscape of Fairness Interventions in Software Engineering Unresolved cited work

Reference 6

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Observation 9918fc89-39b1-4866-a678-ca573e89d077 · outbound

This paper cites {TensorFlow}: a system for {Large-Scale} machine learning.

Exploring the Landscape of Fairness Interventions in Software Engineering {TensorFlow}: a system for {Large-Scale} machine learning

Reference 7

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Observation b64438a4-a8e8-4a93-bea0-22502e19616c · outbound

This paper cites Civil rights act of 1964.

Exploring the Landscape of Fairness Interventions in Software Engineering Civil rights act of 1964

Reference 8

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Observation 547b9459-9f20-4468-9154-4a53503ba4ca · outbound

This paper cites An empirical study on the survival rate of github projects.

Exploring the Landscape of Fairness Interventions in Software Engineering An empirical study on the survival rate of github projects

Reference 9

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Observation 13a2d2ee-2982-4335-a544-11a6b06d9346 · outbound

This paper cites A taxonomy and mapping of computer-based critiquing tools.

Exploring the Landscape of Fairness Interventions in Software Engineering A taxonomy and mapping of computer-based critiquing tools

Reference 10

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Observation 4a6d2710-f29c-45b9-a162-02ecf971c572 · outbound

This paper cites Uncovering and mitigating algorithmic bias through learned latent structure.

Exploring the Landscape of Fairness Interventions in Software Engineering Uncovering and mitigating algorithmic bias through learned latent structure

Reference 11

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Observation debe521a-6e09-4b0d-bb95-7611e38cc82e · outbound

This paper cites Capturing the relationship between sentence triplets for llm and human-generated texts to enhance sentence embeddings.

Exploring the Landscape of Fairness Interventions in Software Engineering Capturing the relationship between sentence triplets for llm and human-generated texts to enhance sentence embeddings

Reference 12

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Observation b76ad8a7-7c34-48f5-af50-55dd8381d64c · outbound

This paper cites Themis: Automatically testing software for discrimination.

Exploring the Landscape of Fairness Interventions in Software Engineering Themis: Automatically testing software for discrimination

Reference 13

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Observation d10647f4-0b9a-49a2-8f37-a33e31bbe313 · outbound

This paper cites Fairness tool evaluation submis- sion 0b7e.

Exploring the Landscape of Fairness Interventions in Software Engineering Fairness tool evaluation submis- sion 0b7e

Reference 14

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Observation aeb74261-b4b7-49fa-8edf-d57827408e28 · outbound

This paper cites Data bias, intelligent systems and criminal justice outcomes.

Exploring the Landscape of Fairness Interventions in Software Engineering Data bias, intelligent systems and criminal justice outcomes

Reference 15

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Observation 3d763bba-a70d-447b-b765-f254a8d89a5a · outbound

This paper cites Putting ai ethics to work: are the tools fit for purpose? AI and Ethics , 2(3):405–429, 2022.

Exploring the Landscape of Fairness Interventions in Software Engineering Putting ai ethics to work: are the tools fit for purpose? AI and Ethics , 2(3):405–429, 2022

Reference 16

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Observation 3685cef2-d4aa-4b8b-accb-c0d6874884f7 · outbound

This paper cites Gpt-4: A Review on Advancements and Opportunities in Natural Language Processing.

Exploring the Landscape of Fairness Interventions in Software Engineering Gpt-4: A Review on Advancements and Opportunities in Natural Language Processing

Reference 17

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Observation 7767c380-04f3-4f2f-aecb-2b9c551fc572 · outbound

This paper cites Themis-ml: A fairness-aware machine learning inter- face for end-to-end discrimination discovery and mitigation.

Exploring the Landscape of Fairness Interventions in Software Engineering Themis-ml: A fairness-aware machine learning inter- face for end-to-end discrimination discovery and mitigation

Reference 18

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Observation 94eb6f43-6167-4ae0-bca8-bfc597a619d4 · outbound

This paper cites Who will leave the company?: a large-scale industry study of developer turnover by mining monthly work report.

Exploring the Landscape of Fairness Interventions in Software Engineering Who will leave the company?: a large-scale industry study of developer turnover by mining monthly work report

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.547047Z

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Observation c89c6845-3103-4c93-801e-420438bf9425 · outbound

This paper cites Social network- ing meets software development: Perspectives from github, msdn, stack exchange, and topcoder.

Exploring the Landscape of Fairness Interventions in Software Engineering Social network- ing meets software development: Perspectives from github, msdn, stack exchange, and topcoder

Reference 20

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Observation f01a6255-3a1d-4e65-b886-330186ebeb1c · outbound

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

Exploring the Landscape of Fairness Interventions in Software Engineering Ai fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias

Reference 21

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Observation 5070ab20-9794-4ad2-bcb6-3699c4ca39e2 · outbound

This paper cites an unresolved cited work.

Exploring the Landscape of Fairness Interventions in Software Engineering Unresolved cited work

Reference 22

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Observation cf8dca04-d277-4307-9ce4-fc033b412765 · outbound

This paper cites an unresolved cited work.

Exploring the Landscape of Fairness Interventions in Software Engineering Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.569238Z

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Observation d48537ae-3ff3-41cf-919e-eef40b60b426 · outbound

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

Exploring the Landscape of Fairness Interventions in Software Engineering Fairlearn: A toolkit for assessing and improving fairness in ai

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.574265Z

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Observation 697144b7-159c-4cb3-8fc6-29f9e0ebba3f · outbound

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

Exploring the Landscape of Fairness Interventions in Software Engineering Do the machine learning models on a crowd sourced platform exhibit bias? an empirical study on model fairness

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.578904Z

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Observation fe8986a8-d76c-46af-b1ac-30b1642afd18 · outbound

This paper cites What’s in a github star? understanding repository starring practices in a social coding platform.

Exploring the Landscape of Fairness Interventions in Software Engineering What’s in a github star? understanding repository starring practices in a social coding platform

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.584552Z

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Observation ad09427d-073c-45ae-8c8f-01edef29091e · outbound

This paper cites Software fairness.

Exploring the Landscape of Fairness Interventions in Software Engineering Software fairness

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.588920Z

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Observation efe1bc3c-2965-4eec-99f1-a881f625306e · outbound

This paper cites GraphQL in action.

Exploring the Landscape of Fairness Interventions in Software Engineering GraphQL in action

Reference 28

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Observation 305e776f-974e-4bee-9ad4-e681f4143a11 · outbound

This paper cites Reuse and maintenance practices among divergent forks in three software ecosystems.

Exploring the Landscape of Fairness Interventions in Software Engineering Reuse and maintenance practices among divergent forks in three software ecosystems

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.600155Z

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Observation e88c09fe-bc60-4786-b63e-668f2567d530 · outbound

This paper cites A clarification of the nuances in the fairness metrics landscape.

Exploring the Landscape of Fairness Interventions in Software Engineering A clarification of the nuances in the fairness metrics landscape

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.604962Z

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Observation 16d12389-5940-41fa-b240-aae2d7085bb5 · outbound

This paper cites Fairness in Machine Learning: A Survey.

Exploring the Landscape of Fairness Interventions in Software Engineering Fairness in Machine Learning: A Survey

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.610952Z

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Observation e0fe5a3b-4d9b-4ef8-99f6-eaa993e489b0 · outbound

This paper cites Fairness in machine learning: A survey.

Exploring the Landscape of Fairness Interventions in Software Engineering Fairness in machine learning: A survey

Reference 32

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Observation aee62d95-6354-4d0f-ae9a-5f8cdaa75d20 · outbound

This paper cites A comprehensive empirical study of bias mitigation methods for machine learning classifiers.

Exploring the Landscape of Fairness Interventions in Software Engineering A comprehensive empirical study of bias mitigation methods for machine learning classifiers

Reference 33

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Observation fe184226-7643-4193-8893-209fffd4ae56 · outbound

This paper cites Fairness improvement with multiple protected attributes: How far are we? In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering , pages 1–13, 2024.

Exploring the Landscape of Fairness Interventions in Software Engineering Fairness improvement with multiple protected attributes: How far are we? In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering , pages 1–13, 2024

Reference 34

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Observation d88859fd-bd9a-41cb-a5c7-73e2da9e8481 · outbound

This paper cites Why modern open source projects fail.

Exploring the Landscape of Fairness Interventions in Software Engineering Why modern open source projects fail

Reference 35

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Observation 30cea050-0791-46bf-96a5-aaed37fa8f2c · outbound

This paper cites Is this github project maintained? measuring the level of maintenance activity of open-source projects.

Exploring the Landscape of Fairness Interventions in Software Engineering Is this github project maintained? measuring the level of maintenance activity of open-source projects

Reference 36

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Observation c73f430d-6307-46d7-bb6d-c24a427cfc1a · outbound

This paper cites Social coding in github: transparency and collaboration in an open software repository.

Exploring the Landscape of Fairness Interventions in Software Engineering Social coding in github: transparency and collaboration in an open software repository

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.641910Z

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Observation 303edd0f-b9eb-4495-911c-68b1267316fb · outbound

This paper cites Sampling projects in github for msr studies.

Exploring the Landscape of Fairness Interventions in Software Engineering Sampling projects in github for msr studies

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.646413Z

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Observation 3d5d3646-1e6d-4f0b-bee4-1c4e829d3de3 · outbound

This paper cites Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights.

Exploring the Landscape of Fairness Interventions in Software Engineering Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.651626Z

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Observation f317e2b1-9288-4693-8f5d-aae56010d029 · outbound

This paper cites Identifying and characterizing unmaintained projects in github.

Exploring the Landscape of Fairness Interventions in Software Engineering Identifying and characterizing unmaintained projects in github

Reference 40

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Observation 60c5bd17-eff1-4ca6-85d9-1d4a0383198e · outbound

This paper cites A taxonomy and catalog of runtime software-fault monitoring tools.

Exploring the Landscape of Fairness Interventions in Software Engineering A taxonomy and catalog of runtime software-fault monitoring tools

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.661100Z

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Observation 93d567d1-480a-4b54-a923-4aec3b649148 · outbound

This paper cites Exploring how machine learning practitioners (try to) use fairness toolkits.

Exploring the Landscape of Fairness Interventions in Software Engineering Exploring how machine learning practitioners (try to) use fairness toolkits

Reference 42

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Observation 014de452-19df-4acc-83d7-1ffd66697ea9 · outbound

This paper cites The eu ai act: a summary of its significance and scope.

Exploring the Landscape of Fairness Interventions in Software Engineering The eu ai act: a summary of its significance and scope

Reference 43

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Observation e99c8a84-6f07-4731-be6b-5c4f0e45d4b4 · outbound

This paper cites Predicting long-time contributors for github projects using machine learning.

Exploring the Landscape of Fairness Interventions in Software Engineering Predicting long-time contributors for github projects using machine learning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.365594Z

Source-reported events for the cited work

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Observation f1e601dd-6e90-41ba-aa8e-a1fdf737cc92 · outbound

This paper cites Certifying and removing dis- parate impact.

Exploring the Landscape of Fairness Interventions in Software Engineering Certifying and removing dis- parate impact

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.350968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2c20e7a1-40ae-443c-a56b-7aa3e1a9c6eb · outbound

This paper cites Gender bias in translation using google translate: Problems and solution.

Exploring the Landscape of Fairness Interventions in Software Engineering Gender bias in translation using google translate: Problems and solution

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.336639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 67dff084-e5b8-4a19-8ff1-13a106414811 · outbound

This paper cites 2020 survey of artificial general intelligence projects for ethics, risk, and policy.

Exploring the Landscape of Fairness Interventions in Software Engineering 2020 survey of artificial general intelligence projects for ethics, risk, and policy

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.318839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c0823745-bbcd-4b6f-86aa-2211ef6bd99d · outbound

This paper cites Practical and open source best practices for ethical machine learning.

Exploring the Landscape of Fairness Interventions in Software Engineering Practical and open source best practices for ethical machine learning

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.301017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 46b70a55-bb3f-436f-9895-101e2d2e2c16 · outbound

This paper cites Fairness testing: testing software for discrimination.

Exploring the Landscape of Fairness Interventions in Software Engineering Fairness testing: testing software for discrimination

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.283299Z

Source-reported events for the cited work

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Observation c89015f8-a025-4b47-ad4c-34f6b534e9f1 · outbound

This paper cites What is Fair? Defining Fairness in Machine Learning for Health.

Exploring the Landscape of Fairness Interventions in Software Engineering What is Fair? Defining Fairness in Machine Learning for Health

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:35:06.269661Z

Source-reported events for the cited work

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Observation a54b116e-f8b3-4c26-8a5a-d70db5fd6551 · outbound

This paper cites Fairness metrics: A comparative analysis.

Exploring the Landscape of Fairness Interventions in Software Engineering Fairness metrics: A comparative analysis

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.267207Z

Source-reported events for the cited work

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Observation bb7e1be5-cb47-4eec-b3ea-35a9671403a4 · outbound

This paper cites Justicia: A stochastic sat approach to formally verify fairness.

Exploring the Landscape of Fairness Interventions in Software Engineering Justicia: A stochastic sat approach to formally verify fairness

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.252000Z

Source-reported events for the cited work

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Observation 9d4fa57d-e687-4ae1-a14d-2810459c9ede · outbound

This paper cites The quest for open source projects that use uml.

Exploring the Landscape of Fairness Interventions in Software Engineering The quest for open source projects that use uml

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.235042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1bd5749c-d018-41af-a0e1-ba837728b563 · outbound

This paper cites Investigating labeler bias in face annotation for machine learning.

Exploring the Landscape of Fairness Interventions in Software Engineering Investigating labeler bias in face annotation for machine learning

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.218882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 59ac072b-e658-4342-8d06-67c7fad4b699 · outbound

This paper cites Olf-ml: An offensive language framework for detection, categorization, and of- fense target identification using text processing and machine learning algorithms.

Exploring the Landscape of Fairness Interventions in Software Engineering Olf-ml: An offensive language framework for detection, categorization, and of- fense target identification using text processing and machine learning algorithms

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.199832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d3bd6595-315e-4868-bd79-d1cfaff081bd · outbound

This paper cites Same file, different changes: the potential of meta-maintenance on github.

Exploring the Landscape of Fairness Interventions in Software Engineering Same file, different changes: the potential of meta-maintenance on github

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.182023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d118e1cd-0fdd-4491-8b4a-519b34752434 · outbound

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

Exploring the Landscape of Fairness Interventions in Software Engineering Fairea: A model behaviour mutation approach to benchmarking bias mitigation methods

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.167110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation efd9a3aa-9418-41c9-a746-8ac05c5a6bab · outbound

This paper cites Fairness-repository-mining-.

Exploring the Landscape of Fairness Interventions in Software Engineering Fairness-repository-mining-

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.152241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ca381fb7-5797-4067-87cb-3525a11d06c8 · outbound

This paper cites Fairness-repository-mining-.

Exploring the Landscape of Fairness Interventions in Software Engineering Fairness-repository-mining-

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.136543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0672d94f-936d-44f3-a6ae-1b4a5c0dc67e · outbound

This paper cites Assurance of machine learning/tinyml in safety-critical domains.

Exploring the Landscape of Fairness Interventions in Software Engineering Assurance of machine learning/tinyml in safety-critical domains

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.120567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d49ffd3e-1032-4270-8cad-b121df271c44 · outbound

This paper cites Github projects.

Exploring the Landscape of Fairness Interventions in Software Engineering Github projects

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.105496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 18d614b9-272e-4266-aa43-346a927649cc · outbound

This paper cites Availability and usage of platform- specific apis: A first empirical study.

Exploring the Landscape of Fairness Interventions in Software Engineering Availability and usage of platform- specific apis: A first empirical study

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.090589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 38e516a3-750f-48b8-9d36-2c8c0aaae84c · outbound

This paper cites Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models.

Exploring the Landscape of Fairness Interventions in Software Engineering Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models

Reference 63

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:35:06.247288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ea42cecc-bd39-4a9b-93b0-b7f66704b363 · outbound

This paper cites Make your tools sparkle with trust: The picse framework for trust in software tools.

Exploring the Landscape of Fairness Interventions in Software Engineering Make your tools sparkle with trust: The picse framework for trust in software tools

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.076139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 87505a5d-2232-47ed-997d-a9a562f1bce7 · outbound

This paper cites Fairkit-learn: a fairness evaluation and comparison toolkit.

Exploring the Landscape of Fairness Interventions in Software Engineering Fairkit-learn: a fairness evaluation and comparison toolkit

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.060934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d137720e-b839-4696-a88f-f998ee12fc6e · outbound

This paper cites Towards ethical data-driven software: filling the gaps in ethics research & practice.

Exploring the Landscape of Fairness Interventions in Software Engineering Towards ethical data-driven software: filling the gaps in ethics research & practice

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.046061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1353d4c8-b674-4831-a51a-287776b7aa62 · outbound

This paper cites Decision theory for discrimination-aware classification.

Exploring the Landscape of Fairness Interventions in Software Engineering Decision theory for discrimination-aware classification

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.030857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4d92ba84-b5df-4485-87ad-90bd8cdd3362 · outbound

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

Exploring the Landscape of Fairness Interventions in Software Engineering Fairness-aware classifier with prejudice remover regularizer

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:07.015215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e81156b3-1a80-4c2c-ae53-99f76404545b · outbound

This paper cites An overview of ethical issues in using ai systems in hiring with a case study of amazon’s ai based hiring tool.

Exploring the Landscape of Fairness Interventions in Software Engineering An overview of ethical issues in using ai systems in hiring with a case study of amazon’s ai based hiring tool

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.999894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eb8e96c3-f608-443a-a47f-d35d1d22b02d · outbound

This paper cites A survey on datasets for fairness-aware machine learning.

Exploring the Landscape of Fairness Interventions in Software Engineering A survey on datasets for fairness-aware machine learning

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.984912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bedd8c86-6771-47af-87b3-6b92b5a2142f · outbound

This paper cites The landscape and gaps in open source fairness toolkits.

Exploring the Landscape of Fairness Interventions in Software Engineering The landscape and gaps in open source fairness toolkits

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.968551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d1a70151-4a83-49e2-8a4d-138ffa932282 · outbound

This paper cites The impact of gdpr on global technology development, 2019.

Exploring the Landscape of Fairness Interventions in Software Engineering The impact of gdpr on global technology development, 2019

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.952735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 482859be-3802-4bcf-8d24-6645ee854e1c · outbound

This paper cites an unresolved cited work.

Exploring the Landscape of Fairness Interventions in Software Engineering Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-08-06T14:35:06.936815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 74a5e7ba-ee61-402b-96f5-bcb017e57a53 · outbound

This paper cites The possessive investment in whiteness: How white people profit from identity politics.

Exploring the Landscape of Fairness Interventions in Software Engineering The possessive investment in whiteness: How white people profit from identity politics

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.921367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 94e44f8b-7875-4ec0-887a-75c77969b6ee · outbound

This paper cites Bias mitigation post-processing for individual and group fairness.

Exploring the Landscape of Fairness Interventions in Software Engineering Bias mitigation post-processing for individual and group fairness

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.905580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c9c7a924-3e26-4218-ac10-3a403f1db78c · outbound

This paper cites Assessing the fairness of ai systems: Ai practitioners’ processes, challenges, and needs for support.

Exploring the Landscape of Fairness Interventions in Software Engineering Assessing the fairness of ai systems: Ai practitioners’ processes, challenges, and needs for support

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.889972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1fbaa55e-d1b8-4775-9b6f-6e342f8f7874 · outbound

This paper cites Survey on Causal-based Machine Learning Fairness Notions.

Exploring the Landscape of Fairness Interventions in Software Engineering Survey on Causal-based Machine Learning Fairness Notions

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.829399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba10c656-e5cb-437e-9601-f9a2803db696 · outbound

This paper cites On the applicability of machine learning fairness notions.

Exploring the Landscape of Fairness Interventions in Software Engineering On the applicability of machine learning fairness notions

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.875525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7b90d393-28d6-4a6d-a0d8-ab532c983c33 · outbound

This paper cites A tax- onomy of tools and approaches for fairification.

Exploring the Landscape of Fairness Interventions in Software Engineering A tax- onomy of tools and approaches for fairification

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.860401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 210a1c31-b320-4da0-9102-44697742681b · outbound

This paper cites Ethical issues in focus by the autonomous vehicles industry.

Exploring the Landscape of Fairness Interventions in Software Engineering Ethical issues in focus by the autonomous vehicles industry

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.846138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 988a283e-c812-42fd-bd93-11f33fa8f6a3 · outbound

This paper cites Mining co-change information to understand when build changes are necessary.

Exploring the Landscape of Fairness Interventions in Software Engineering Mining co-change information to understand when build changes are necessary

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.831421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6c4f2304-ea2c-464f-8f10-6cbba1ecb76f · outbound

This paper cites Statistical methods for reliability data.

Exploring the Landscape of Fairness Interventions in Software Engineering Statistical methods for reliability data

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.816599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d86608f1-65dd-44b2-bb8f-1652c3db6c32 · outbound

This paper cites A survey on bias and fairness in machine learning.

Exploring the Landscape of Fairness Interventions in Software Engineering A survey on bias and fairness in machine learning

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.801715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 628c632c-0f04-4cfc-ad9a-2eaf1a1ac7cd · outbound

This paper cites A taxonomy of machine learning fairness tool specifications, features and workflows.

Exploring the Landscape of Fairness Interventions in Software Engineering A taxonomy of machine learning fairness tool specifications, features and workflows

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.785385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cde4c25d-e5fb-4d39-93e4-18410edf92b2 · outbound

This paper cites Peer interaction effectively, yet infrequently, enables programmers to discover new tools.

Exploring the Landscape of Fairness Interventions in Software Engineering Peer interaction effectively, yet infrequently, enables programmers to discover new tools

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.769304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9cc0cc15-6d1a-4349-b208-8b58399ebefb · outbound

This paper cites An automated approach to assess the similarity of github repositories.

Exploring the Landscape of Fairness Interventions in Software Engineering An automated approach to assess the similarity of github repositories

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.754493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7b9ff618-7caf-446c-ba57-ad596b032a35 · outbound

This paper cites From literature to practice: Exploring fairness testing tools for the software industry adoption.

Exploring the Landscape of Fairness Interventions in Software Engineering From literature to practice: Exploring fairness testing tools for the software industry adoption

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.739386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 981edce8-8d65-4976-8b90-497208909ffd · outbound

This paper cites Assessing and mitigating bias in medical artificial intelligence: the effects of race and ethnicity on a deep learning model for ecg analysis.

Exploring the Landscape of Fairness Interventions in Software Engineering Assessing and mitigating bias in medical artificial intelligence: the effects of race and ethnicity on a deep learning model for ecg analysis

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.724244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b8144a11-7f2f-4814-8cc5-5f207b580ed4 · outbound

This paper cites Bias and unfairness in machine learning models: a systematic review on datasets, tools, fairness metrics, and identification and mitigation methods.

Exploring the Landscape of Fairness Interventions in Software Engineering Bias and unfairness in machine learning models: a systematic review on datasets, tools, fairness metrics, and identification and mitigation methods

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.707992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 25837898-0560-432b-871d-26d33a0e763f · outbound

This paper cites Scikit-learn: Machine learning in python.

Exploring the Landscape of Fairness Interventions in Software Engineering Scikit-learn: Machine learning in python

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.691957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f9b5a11c-a38a-4156-a8fb-425afa5ca628 · outbound

This paper cites A review on fairness in machine learning.

Exploring the Landscape of Fairness Interventions in Software Engineering A review on fairness in machine learning

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.677287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c4b23e8f-8f1f-4326-9b3a-ce1f14672657 · outbound

This paper cites an unresolved cited work.

Exploring the Landscape of Fairness Interventions in Software Engineering Unresolved cited work

Reference 92

Resolution: unresolved; raw_fallback, observed 2026-08-06T14:35:06.662459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7c5fb4d5-7b50-42ba-8d1f-4f72b8c72e71 · outbound

This paper cites Towards fairness in practice: A practitioner-oriented rubric for evaluating fair ml toolkits.

Exploring the Landscape of Fairness Interventions in Software Engineering Towards fairness in practice: A practitioner-oriented rubric for evaluating fair ml toolkits

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.647712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0a4b1f41-8d75-496d-9f59-d9d5073b1684 · outbound

This paper cites A Framework for Fairness: A Systematic Review of Existing Fair AI Solutions.

Exploring the Landscape of Fairness Interventions in Software Engineering A Framework for Fairness: A Systematic Review of Existing Fair AI Solutions

Reference 94

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:35:06.204127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ff799b9d-bce1-4778-bc2c-27136ede3925 · outbound

This paper cites Estimating development effort in free/open source software projects by mining software repos- itories: a case study of openstack.

Exploring the Landscape of Fairness Interventions in Software Engineering Estimating development effort in free/open source software projects by mining software repos- itories: a case study of openstack

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.632832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation da174c97-f125-4c7f-8ced-9f250a29d26a · outbound

This paper cites {SourceFinder}: Finding malware {Source-Code} from publicly available repositories in {GitHub}.

Exploring the Landscape of Fairness Interventions in Software Engineering {SourceFinder}: Finding malware {Source-Code} from publicly available repositories in {GitHub}

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.617738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bfc9b121-8130-4420-8662-b189ff180f73 · outbound

This paper cites Aequitas: A Bias and Fairness Audit Toolkit.

Exploring the Landscape of Fairness Interventions in Software Engineering Aequitas: A Bias and Fairness Audit Toolkit

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:05.931275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2398dc1-1840-4b26-b619-27126a7dcf80 · outbound

This paper cites Towards mining norms in open source software repositories.

Exploring the Landscape of Fairness Interventions in Software Engineering Towards mining norms in open source software repositories

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.602394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ca7f3341-ef1d-43cc-93a9-7a0e5073028d · outbound

This paper cites Discriminatory effect and the fair housing act.

Exploring the Landscape of Fairness Interventions in Software Engineering Discriminatory effect and the fair housing act

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.587083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ddce4f8f-e782-489b-9c40-b70263048e52 · outbound

This paper cites Towards efficient software engineering in the era of ai and ml: Best practices and challenges.

Exploring the Landscape of Fairness Interventions in Software Engineering Towards efficient software engineering in the era of ai and ml: Best practices and challenges

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:35:06.571639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers