Fairness in Federated Learning: Fairness for Whom? | Paper Citation Record

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Fairness in Federated Learning: Fairness for Whom? , " * write output.state after.block = add.period write newline

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Fairness in Federated Learning: Fairness for Whom? write newline

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Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

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Fairness in Federated Learning: Fairness for Whom? Mitigating Bias in Federated Learning

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Fairness in Federated Learning: Fairness for Whom? A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms

Reference 5

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Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

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Fairness in Federated Learning: Fairness for Whom? T.; Klous, S.; and Gommans, L

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This paper cites Fairness and Privacy in Federated Learning and Their Implications in Healthcare.

Fairness in Federated Learning: Fairness for Whom? Fairness and Privacy in Federated Learning and Their Implications in Healthcare

Reference 10

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This paper cites S.; Andr \'e da Costa, C.; K \"u derle, A.; Yari, I.

Fairness in Federated Learning: Fairness for Whom? S.; Andr \'e da Costa, C.; K \"u derle, A.; Yari, I

Reference 11

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Fairness in Federated Learning: Fairness for Whom? N.; Dieng, A.; Haykel, I.; Rostamzadeh, N.; Pfohl, S.; Nagpal, C.; Nagawa, M.; Oppong, A.; Koyejo, S.; and Heller, K

Reference 12

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This paper cites A Multivocal Literature Review on Privacy and Fairness in Federated Learning.

Fairness in Federated Learning: Fairness for Whom? A Multivocal Literature Review on Privacy and Fairness in Federated Learning

Reference 14

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Fairness in Federated Learning: Fairness for Whom? C.; Gabriel, I.; and Mohamed, S

Reference 15

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Fairness in Federated Learning: Fairness for Whom? Towards Federated Learning at Scale: System Design

Reference 16

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This paper cites Enhancing Privacy in the Early Detection of Sexual Predators Through Federated Learning and Differential Privacy.

Fairness in Federated Learning: Fairness for Whom? Enhancing Privacy in the Early Detection of Sexual Predators Through Federated Learning and Differential Privacy

Reference 17

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Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 18

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Fairness in Federated Learning: Fairness for Whom? J.; Wang, J.; and Joshi, G

Reference 19

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This paper cites FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data.

Fairness in Federated Learning: Fairness for Whom? FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data

Reference 20

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This paper cites Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks.

Fairness in Federated Learning: Fairness for Whom? Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks

Reference 21

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This paper cites S.; and Brinton, C.

Fairness in Federated Learning: Fairness for Whom? S.; and Brinton, C

Reference 22

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Fairness in Federated Learning: Fairness for Whom? Debiasing Vision-Language Models via Biased Prompts

Reference 23

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Reference 24

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Fairness in Federated Learning: Fairness for Whom? Models of fairness in federated learning

Reference 26

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Fairness in Federated Learning: Fairness for Whom? B.; Megdiche, I.; Peninou, A.; and Teste, O

Reference 27

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Fairness in Federated Learning: Fairness for Whom? FairFed: Enabling Group Fairness in Federated Learning

Reference 28

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Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

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Fairness in Federated Learning: Fairness for Whom? O.; Rossi, R

Reference 30

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Fairness in Federated Learning: Fairness for Whom? Mitigating System Bias in Resource Constrained Asynchronous Federated Learning Systems

Reference 31

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Fairness in Federated Learning: Fairness for Whom? Active Federated Learning

Reference 32

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Fairness in Federated Learning: Fairness for Whom? Enforcing fairness in private federated learning via the modified method of differential multipliers

Reference 34

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Fairness in Federated Learning: Fairness for Whom? U.; Qureshi, R.; Shah, A.; Irfan, M.; Zafar, A.; Shaikh, M

Reference 35

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Fairness in Federated Learning: Fairness for Whom? Federated Learning for Mobile Keyboard Prediction

Reference 36

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Fairness in Federated Learning: Fairness for Whom? An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee

Reference 37

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Fairness in Federated Learning: Fairness for Whom? FedFair^3: Unlocking Threefold Fairness in Federated Learning

Reference 38

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Fairness in Federated Learning: Fairness for Whom? S.; and Chen, L

Reference 39

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Fairness in Federated Learning: Fairness for Whom? B.; Avent, B.; Bellet, A.; Bennis, M.; Bhagoji, A

Reference 40

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Fairness in Federated Learning: Fairness for Whom? A Comprehensive Study on Model Initialization Techniques Ensuring Efficient Federated Learning

Reference 41

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Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 43

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Fairness in Federated Learning: Fairness for Whom? Federated Learning: Strategies for Improving Communication Efficiency

Reference 44

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Fairness in Federated Learning: Fairness for Whom? Geographical Node Clustering and Grouping to Guarantee Data IIDness in Federated Learning

Reference 46

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Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 47

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Fairness in Federated Learning: Fairness for Whom? Fair Resource Allocation in Federated Learning

Reference 48

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Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

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Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 53

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Fairness in Federated Learning: Fairness for Whom? How to avoid machine learning pitfalls: a guide for academic researchers

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Fairness in Federated Learning: Fairness for Whom? K.; and Wan, S

Reference 55

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Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

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Fairness in Federated Learning: Fairness for Whom? Collaborative Fairness in Federated Learning

Reference 57

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Fairness in Federated Learning: Fairness for Whom? U.; Jeslin, J

Reference 58

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This paper cites Achieving Fairness Across Local and Global Models in Federated Learning.

Fairness in Federated Learning: Fairness for Whom? Achieving Fairness Across Local and Global Models in Federated Learning

Reference 59

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Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 61

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Unavailable: canonical work link unavailable.

Observation 7503403b-8c36-450d-94b2-df78a59d1ca6 · outbound

This paper cites GLOCALFAIR: Jointly Improving Global and Local Group Fairness in Federated Learning.

Fairness in Federated Learning: Fairness for Whom? GLOCALFAIR: Jointly Improving Global and Local Group Fairness in Federated Learning

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:18.504382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04f2fd2a-db5d-4cf6-ae0a-06da1ee993c7 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:29.954739Z

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 28cc8a6e-874e-440b-8f0a-b4c89f85c74b · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:18.621610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9db4a232-8879-4900-a22a-cc6b566e7525 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:29.800480Z

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 5d3c91f0-9a04-40f1-a45e-28b9c6de62f5 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:29.645112Z

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 96a15e76-9bf9-4845-821e-a88130752442 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:29.483775Z

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 30d42717-556f-41c4-a186-0afe835d3be4 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:29.328965Z

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 76aff948-2f79-466b-933c-450e3cdecfaf · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 69

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:29.170320Z

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 f325ea29-df31-4085-b462-efd669250940 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:29.061028Z

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 79e31d50-fb8e-4696-ad18-76ac7dc087ca · outbound

This paper cites PrivFairFL: Privacy-Preserving Group Fairness in Federated Learning.

Fairness in Federated Learning: Fairness for Whom? PrivFairFL: Privacy-Preserving Group Fairness in Federated Learning

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:19.025872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a75912c-c3af-4354-8c8f-faedd731d4d1 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:28.919711Z

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 ecffebf1-81e6-4f5a-9f34-0243da77f9f0 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:28.806704Z

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 9ef13a09-d263-4463-86b2-7a415ac77fa2 · outbound

This paper cites H.; Noor, F.

Fairness in Federated Learning: Fairness for Whom? H.; Noor, F

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:28.645326Z

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 d871605c-f036-4546-8d2d-bf9433847055 · outbound

This paper cites D.; Kumar, I.

Fairness in Federated Learning: Fairness for Whom? D.; Kumar, I

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:28.507564Z

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 57a2afa1-ba6a-4167-abd1-6a29ebc2af5f · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 76

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:28.381589Z

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 ae42e2d5-2d45-4060-b0e1-cc18485b31f9 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:19.405215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd7b9706-d8fa-42c3-95a5-05aaad7fa936 · outbound

This paper cites A Survey on Group Fairness in Federated Learning: Challenges, Taxonomy of Solutions and Directions for Future Research.

Fairness in Federated Learning: Fairness for Whom? A Survey on Group Fairness in Federated Learning: Challenges, Taxonomy of Solutions and Directions for Future Research

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:19.485853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6081441-d3df-48cb-a1d3-d986226ceda9 · outbound

This paper cites M.; Hoang, D.

Fairness in Federated Learning: Fairness for Whom? M.; Hoang, D

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:28.253756Z

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 1ff37a40-b5ee-44c7-a392-c39c58acb188 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 80

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:28.083084Z

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 1fca711b-251a-475d-9cfc-76d6d36b5d89 · outbound

This paper cites A.; Huang, K.; DeFilippis, E.; Radanovic, G.; Parkes, D.

Fairness in Federated Learning: Fairness for Whom? A.; Huang, K.; DeFilippis, E.; Radanovic, G.; Parkes, D

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:27.934106Z

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 18d205db-7379-4c4e-b354-044d878fb4bf · outbound

This paper cites D.; Boyd, D.; Friedler, S.

Fairness in Federated Learning: Fairness for Whom? D.; Boyd, D.; Friedler, S

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:19.787571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a7f0eb9-64e4-479e-a37a-8ce5543e4792 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 83

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:27.783452Z

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 f21e4a86-b698-473c-ae10-4a97b2a8b773 · outbound

This paper cites Mitigating Group Bias in Federated Learning for Heterogeneous Devices.

Fairness in Federated Learning: Fairness for Whom? Mitigating Group Bias in Federated Learning for Heterogeneous Devices

Reference 84

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:45:22.324066Z

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 055b7783-b22d-41b7-a264-f7ce1fdb27f7 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:19.977668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9fc5ceb-eeec-4aa2-b98d-36b26155d542 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 86

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:27.659315Z

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 02bbd656-7292-48fe-a197-5e0bd11cf816 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 87

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:27.529633Z

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 5ac8b6bc-8d99-478d-807d-2b38019f56e1 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:27.408949Z

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 a02d790a-9e83-4a3b-85e1-620295f04e64 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 89

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:27.279799Z

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 b501b176-b083-4fb4-a26b-14969c1fde22 · outbound

This paper cites Z.; Yu, H.; Cui, L.; and Yang, Q.

Fairness in Federated Learning: Fairness for Whom? Z.; Yu, H.; Cui, L.; and Yang, Q

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:27.169520Z

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 4a586798-2dab-45c8-bd2f-cf3419e703b2 · outbound

This paper cites Understanding Unintended Memorization in Federated Learning.

Fairness in Federated Learning: Fairness for Whom? Understanding Unintended Memorization in Federated Learning

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:20.458788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce5048e7-2379-4a5e-a6d6-f38feab803af · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 92

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:27.033128Z

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 d1975b97-cb96-4c86-977a-4f949ee902dc · outbound

This paper cites T.; Roy, K.; and Yuan, X.

Fairness in Federated Learning: Fairness for Whom? T.; Roy, K.; and Yuan, X

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:45:26.879406Z

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 58d0df42-a33b-4ed2-a601-504ae349f6ba · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 94

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:26.720974Z

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 16d627c7-4562-4b19-9aa7-dcfe39bd777f · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 95

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:26.595484Z

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 6963d7a6-70e0-413d-998d-7f79e7f0bffc · outbound

This paper cites Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives.

Fairness in Federated Learning: Fairness for Whom? Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives

Reference 96

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:45:22.191682Z

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 a400d598-f6d7-4dbf-b118-74f740795264 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 97

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:26.480522Z

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 bb5b136d-9e10-4987-b2df-9c880839da47 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 98

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:26.373157Z

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 e0a88d38-88a4-4769-a690-eda4d37d6699 · outbound

This paper cites an unresolved cited work.

Fairness in Federated Learning: Fairness for Whom? Unresolved cited work

Reference 99

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:45:26.242658Z

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 afc55310-fa90-4aa6-8d13-914b9feee17d · outbound

This paper cites Achieving Fairness in Dermatological Disease Diagnosis through Automatic Weight Adjusting Federated Learning and Personalization.

Fairness in Federated Learning: Fairness for Whom? Achieving Fairness in Dermatological Disease Diagnosis through Automatic Weight Adjusting Federated Learning and Personalization

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:21.109483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers