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Paper Citation Record · LEDGER

Fairness in Federated Learning: Fairness for Whom?

As of 18 August 2026, this Paper Citation Record lists 100 of 110 outbound references and 0 inbound Pith citation observations for arXiv:2505.21584.

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

pith.paper-citation-record.v1
2505.21584 v1

Coverage vector

measured 100 of 110 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:45:21.109483Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

100 of 110 outbound references displayed

  • verified exact14
  • verified fuzzy8
  • unresolved77
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9a3c2957-e100-4224-bbc0-93508933f1e2 · outbound

This paper cites , " * write output.state after.block = add.period write newline.

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

Reference 1

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Observation 6556b2b0-bdc3-4853-bb27-a2fb4c1cac28 · outbound

This paper cites write newline.

Fairness in Federated Learning: Fairness for Whom? write newline

Reference 2

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source=arxiv_source observed=2026-08-07T13:45:11.700561Z digest=sha256:4f4c20a511bdd51628b31f525435dd9eba624b1ee14cdc4d686d565f2b70ab34

Observation af6d1286-53e1-4f5e-b000-aa45c89a6e8a · outbound

This paper cites an unresolved cited work.

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

Reference 3

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source=arxiv_source observed=2026-08-07T13:45:11.755588Z digest=sha256:c7e95f512a07131a5b4804efbc26c3b0712af2065aac2b04e5537940dd81bbb0

Observation 9c088de3-3582-46d8-aaa4-5674c9ffa7ee · outbound

This paper cites Mitigating Bias in Federated Learning.

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

Reference 4

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source=arxiv_source observed=2026-08-07T13:45:11.863888Z digest=sha256:795efff58404c62bb4a24c145e578c370fd886fa8d4ee8f872a8305bfe2a241f

Observation 8503c80f-0aea-4faf-ac35-453729c25172 · outbound

This paper cites A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms.

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

Reference 5

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source=arxiv_source observed=2026-08-07T13:45:12.005642Z digest=sha256:8cbfc89ed93d2ef0efc737c36d58a75cc7b754a454789ce16dfbc6b45a48124d

Observation b920c005-c3ae-4733-af1f-dcd10c224f98 · outbound

This paper cites an unresolved cited work.

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

Reference 6

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source=arxiv_source observed=2026-08-07T13:45:12.123327Z digest=sha256:0aff63c5a75d30b83cfc90a1e8aa1c6ff0269f00e854f55c8b277a55f6ccb2f5

Observation 60fd0177-d8e5-4b6d-99c0-457936bfa7cc · outbound

This paper cites an unresolved cited work.

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

Reference 7

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Observation cabbcce5-4d39-4443-b119-761880bee71f · outbound

This paper cites T.; Klous, S.; and Gommans, L.

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

Reference 8

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source=arxiv_source observed=2026-08-07T13:45:12.305584Z digest=sha256:6a305a51015c4f0cc111d65e65fdfbb11d53b6cb9790ede8d0c821487ae8e8df

Observation b3598c63-07fd-45b4-bd54-aa1bd4e6408f · outbound

This paper cites an unresolved cited work.

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

Reference 9

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source=arxiv_source observed=2026-08-07T13:45:12.445668Z digest=sha256:3ffe9e93e95933dba0312ae40a09cf7772e52416f351bd44d0d404680d7c70fb

Observation 8a30756b-a19a-412d-8fca-05d17064eb26 · outbound

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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local_arxiv, observed 2026-08-07T13:45:24.766577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:12.541625Z digest=sha256:fe7f697077d3eee5f6384cbc430ff673498b2b5a109f20f41d5c8b4fd9597fbe

Observation f3e3f73a-5441-4e79-924c-39ab57688535 · outbound

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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source=arxiv_source observed=2026-08-07T13:45:12.641194Z digest=sha256:856f8aa2554932445cc23e58db77790907632421e7878e9d76eaf96622727902

Observation 0b1acea8-5300-4ff0-a558-f090f5d1a506 · outbound

This paper cites N.; Dieng, A.; Haykel, I.; Rostamzadeh, N.; Pfohl, S.; Nagpal, C.; Nagawa, M.; Oppong, A.; Koyejo, S.; and Heller, K.

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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source=arxiv_source observed=2026-08-07T13:45:12.727880Z digest=sha256:c0bd6c144e9d002fb058b60256e48a029c9306c6ad2c9ae7e2e67a5774f4acf9

Observation 62a5b16a-9eae-424f-87ce-fdff703411d5 · outbound

This paper cites an unresolved cited work.

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

Reference 13

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source=arxiv_source observed=2026-08-07T13:45:12.888469Z digest=sha256:0fbcb988c1af1033ddb4d1d07997901af9452e76338217ada4ca5c6d6bfac85d

Observation bea3d18d-a63f-4f70-a5e0-c0fe64271ea9 · outbound

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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local_arxiv, observed 2026-08-07T13:45:24.609259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:12.981649Z digest=sha256:ad2b68efb27397f853acacb73c0f277f0e000bd52822196d2d3de6f2f4e92966

Observation c7fcc6c2-ff42-4f30-b83d-f72e0223bbcb · outbound

This paper cites C.; Gabriel, I.; and Mohamed, S.

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

Reference 15

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source=arxiv_source observed=2026-08-07T13:45:13.046080Z digest=sha256:4687e2e5a8291f9abc94794fa4c0098a0084c1153b240aa73dc82237ea133eda

Observation 6e3291f8-816a-4b19-949c-d847c2673f1b · outbound

This paper cites Towards Federated Learning at Scale: System Design.

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

Reference 16

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source=arxiv_source observed=2026-08-07T13:45:13.106313Z digest=sha256:cc4bcb12c122cb809dcd14999f1c7bdbc4a436eb2c2e251e0d2de1b650391902

Observation 12964c67-4b31-4a75-be7e-1a643fa33bb1 · outbound

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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local_arxiv, observed 2026-08-07T13:45:24.440153Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:13.210150Z digest=sha256:47714f497f4874f64a87bae13d660ec7073e2b82eff50dd38bbbb3f5d380889c

Observation 1db632b6-0b53-4f55-b2e8-991257aeabf3 · outbound

This paper cites an unresolved cited work.

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

Reference 18

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source=arxiv_source observed=2026-08-07T13:45:13.333361Z digest=sha256:a2be54c63483d0197c8cbdc188e4f78b1ec969a4f368f36a43a272389f7d2dd8

Observation 58c6b3e2-444f-4e2e-b65c-d404945db59d · outbound

This paper cites J.; Wang, J.; and Joshi, G.

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

Reference 19

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source=arxiv_source observed=2026-08-07T13:45:13.445822Z digest=sha256:b2ae1d73b67f3d038ba0ed17a304456e16cd421215ff11ff0c80e8509ff50ed2

Observation f428acd0-89d1-407e-b648-88d176983777 · outbound

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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local_arxiv, observed 2026-08-07T13:45:24.291299Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:13.601270Z digest=sha256:fb2fb0b49e44dd74ae0d3e448291870ff9494b0627c28f3cfc9587b2504499e3

Observation dcc34208-aa18-48fd-992d-0e9dac9e4bab · outbound

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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local_arxiv, observed 2026-08-07T13:45:24.159056Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:13.677474Z digest=sha256:245811a33d606bcc0f0af40c3d5bef2b641db408e3875369feb84bfb34187849

Observation 6a4700d5-f911-4a0d-8af1-ec24fd784e7f · outbound

This paper cites S.; and Brinton, C.

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

Reference 22

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source=arxiv_source observed=2026-08-07T13:45:13.745486Z digest=sha256:3c8a166c9f547be0626ff8ebce77f6fe81b3a37e5d63280cc665f76580c18fb3

Observation 632a5265-1b66-44af-9072-7488936a6d77 · outbound

This paper cites Debiasing Vision-Language Models via Biased Prompts.

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

Reference 23

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Observation 403e6787-a77a-4baf-a8a3-0840f3d2501f · outbound

This paper cites an unresolved cited work.

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

Reference 24

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source=arxiv_source observed=2026-08-07T13:45:13.924531Z digest=sha256:92e575177df487e87d07204c41298b6d26aeae28018ee7465fa28b83d4ebeb25

Observation 4809bc06-b802-4021-afed-c41798af5f3e · outbound

This paper cites an unresolved cited work.

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

Reference 25

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source=arxiv_source observed=2026-08-07T13:45:14.043854Z digest=sha256:a1dd21739271cc31e9a4b5d6465a373d5540cb73a54f66a7e25c339ecbd03d41

Observation a39c1d8c-11cb-4c4b-82e3-89d491d9ed8b · outbound

This paper cites Models of fairness in federated learning.

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

Reference 26

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local_arxiv, observed 2026-08-07T13:45:24.022267Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:14.158388Z digest=sha256:9668534de929f61ed4791d133f7e2166ca00f4cdce098ac383539e531ef797a5

Observation 1ddebbf4-6a97-40ff-b99a-1db970d72445 · outbound

This paper cites B.; Megdiche, I.; Peninou, A.; and Teste, O.

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

Reference 27

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raw_fallback, observed 2026-08-07T13:45:23.887578Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:14.262627Z digest=sha256:d9508dae36190274bedfdbcf8f7ac6983912448fb3c4bff0e1ecce5069481fe6

Observation 18cd5bd7-884d-4216-bf58-92af6f287a9b · outbound

This paper cites FairFed: Enabling Group Fairness in Federated Learning.

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

Reference 28

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source=arxiv_source observed=2026-08-07T13:45:14.382043Z digest=sha256:d10e98e34a3f812dbd3ad5690728f1dd500f67bd7b0de826f12f2f4a732f516f

Observation 5b7b6a76-a348-49c9-b071-14800aa97e53 · outbound

This paper cites an unresolved cited work.

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

Reference 29

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Observation 66923e66-c10a-4773-a738-30b84d0cee6e · outbound

This paper cites O.; Rossi, R.

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

Reference 30

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source=arxiv_source observed=2026-08-07T13:45:14.541788Z digest=sha256:32b3462abde1e3efd3e750af691e4c31d6e73ee9e3516c2a831f4cbc36dbda4c

Observation b523afe3-3dfc-42cd-bd82-543ed743ba9e · outbound

This paper cites Mitigating System Bias in Resource Constrained Asynchronous Federated Learning Systems.

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

Reference 31

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local_arxiv, observed 2026-08-07T13:45:23.513322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:14.638189Z digest=sha256:3f781af65de99dd902a2ef785130a452f790d32ab391649cd0500e456c9b3fa9

Observation 090b125a-b7fc-4b19-b200-9224f1091d39 · outbound

This paper cites Active Federated Learning.

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

Reference 32

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source=arxiv_source observed=2026-08-07T13:45:14.767471Z digest=sha256:65125787dc8d208aa01182bfd586b81ab64cb057aedb54c4ffa0b08a097b04c2

Observation b47cd77a-2365-4d0b-9f05-db4d4adbae2c · outbound

This paper cites an unresolved cited work.

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

Reference 33

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Observation 16acdc75-3b1c-4ba1-967c-e157bf78469e · outbound

This paper cites Enforcing fairness in private federated learning via the modified method of differential multipliers.

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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Observation d63433af-a1a1-40d6-9c1a-7347cb746bcd · outbound

This paper cites U.; Qureshi, R.; Shah, A.; Irfan, M.; Zafar, A.; Shaikh, M.

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

Reference 35

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Observation 63d95728-af72-45da-8ba8-cb09c6bb1579 · outbound

This paper cites Federated Learning for Mobile Keyboard Prediction.

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

Reference 36

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source=arxiv_source observed=2026-08-07T13:45:15.197601Z digest=sha256:54f0fd392a247446c6d36ab4274875e61162a0a5be1e13a62cc25ea3a8d8a78d

Observation 8995af0f-c61d-42e0-96e6-da473046d42d · outbound

This paper cites An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee.

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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local_arxiv, observed 2026-08-07T13:45:23.331492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:15.293922Z digest=sha256:1fb4d6d74242f00d1d8e83091eab8c718153432ee3cc3fc5415700b4444829ed

Observation 15700eb6-a92b-479d-bb12-9f54a2330341 · outbound

This paper cites FedFair^3: Unlocking Threefold Fairness in Federated Learning.

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

Reference 38

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verified exact
local_arxiv, observed 2026-08-07T13:45:23.213578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:15.394658Z digest=sha256:a90c6b36140f6a5977f43cd38ba05b48e114163cdf3ce1e0463dea50dc422cd7

Observation 494d1f1d-f6d6-4720-80dd-21aa4e75b7ad · outbound

This paper cites S.; and Chen, L.

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

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:15.531504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:15.531504Z digest=sha256:41dd23213097617df0b8a03f566505c5a7c80316426d90294d4f674b9218ea50

Observation 674167f6-e375-4a6d-ab1d-7d2e185442ca · outbound

This paper cites B.; Avent, B.; Bellet, A.; Bennis, M.; Bhagoji, A.

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

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:15.640874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:15.640874Z digest=sha256:4a50101df18be551f6ecb8ab81d00cd9d15c3914b6ddb4727d1e20f6ce19500a

Observation aa2904ac-fc2b-40bd-ad91-15dd968da8ff · outbound

This paper cites A Comprehensive Study on Model Initialization Techniques Ensuring Efficient Federated Learning.

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

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:45:23.088088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:15.734030Z digest=sha256:9c28da8db245c308c6e0d73f077c05a3bbdc0aa59afb40ea3802e881fec98dcd

Observation 41db02cf-333b-42c1-9719-e363fbfdae4d · outbound

This paper cites an unresolved cited work.

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

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:15.873754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:15.873754Z digest=sha256:a5b05f62311993f2339ecb6c5875e19b360fe0315bf3746b3f7b0168a9df6195

Observation d666a399-40e3-4f37-91cc-4b7784a629a1 · outbound

This paper cites an unresolved cited work.

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

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:15.980357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:15.980357Z digest=sha256:5880a9d1d4011876f0aab3cd8168e1c9aa9b6be9e5cb44e173f2011359ed6d2f

Observation d1e68267-0e1e-4f04-9c64-0f621f156647 · outbound

This paper cites Federated Learning: Strategies for Improving Communication Efficiency.

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

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:16.087427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:16.087427Z digest=sha256:146c8984c0b20ca4698176e63729a47975eafe0bc40274c78f3e239886342a78

Observation 392b05da-85fd-4068-8836-dfa2290c9c64 · outbound

This paper cites an unresolved cited work.

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

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:16.323616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:16.323616Z digest=sha256:b423290e9afefa561892207d8c1aa8866a6089cf5d0eb82b91ae5033d81f1202

Observation e4d53be9-168e-4a95-886b-8180ae352965 · outbound

This paper cites Geographical Node Clustering and Grouping to Guarantee Data IIDness in Federated Learning.

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

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:45:22.947532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:16.814656Z digest=sha256:1700d2fb3c72b2c2b2acae669539713f2b35687caa464bf4af273737596f5cab

Observation e7c19239-ab44-40c6-8cfb-66410ec29d36 · outbound

This paper cites an unresolved cited work.

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

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:17.418466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:17.418466Z digest=sha256:7f1aef698ef33aa5f6a4ea180ef5c59bac3402d8e15ad0e02ce6a63829e28ebd

Observation 70844dd3-43cf-43dd-bb67-8aa118e39c38 · outbound

This paper cites Fair Resource Allocation in Federated Learning.

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

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:17.526795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:17.526795Z digest=sha256:7cb105a5d822d11d72af8437c2d2afbc48bb1b112885b84b69c62e9ca637756b

Observation ad6528d6-1e7c-4111-b5cd-168474ad6271 · outbound

This paper cites an unresolved cited work.

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

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:17.565512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:17.565512Z digest=sha256:c6964427cc047d8c4132ccea21decc4dfb7c0654ed101a13f87a7f28b045bc3f

Observation c4425f40-744a-4d31-8bf8-924344e8b7ba · outbound

This paper cites an unresolved cited work.

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

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:17.641650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:17.641650Z digest=sha256:44e268fc4eeb1158f8c6d671ef132a6ecd7d67ad51479dcc6da03c349a473ae9

Observation fa3ad831-e1e2-4c18-9e85-3e50f578675d · outbound

This paper cites an unresolved cited work.

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

Reference 51

Resolution
verified exact
raw_fallback, observed 2026-08-07T13:45:22.764936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:17.750524Z digest=sha256:34366700a7f5cc402539e5972c87611183e3a874fde27e8f7f018c33e0ab0a3b

Observation 79e5fce9-3261-4b2f-be70-70b299d0f9b7 · outbound

This paper cites an unresolved cited work.

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

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:17.876342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:17.876342Z digest=sha256:c3761e5b94c716b6f484bfbae96678bb6c20a0cb31f768138e3fd451daebf126

Observation d8645930-bfe0-4240-8d59-31a224541984 · outbound

This paper cites an unresolved cited work.

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

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:17.992198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:17.992198Z digest=sha256:f27b2caaef4d95be840f14ac204b31c23a65561f14a760c33d076a39a6c45a26

Observation c799a58f-57de-42e6-a190-97f981c357ab · outbound

This paper cites How to avoid machine learning pitfalls: a guide for academic researchers.

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

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:18.043579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:18.043579Z digest=sha256:5a9e0e590ad56fd21211abf347ef41c7d0bc727bf1c26d82ef718f0fa3f379a8

Observation 2b1cec90-0d23-4dd2-a7e4-6d87e808d855 · outbound

This paper cites K.; and Wan, S.

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

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:45:30.573667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:18.105541Z digest=sha256:198937e5dfee837b804097379bb06db5bd07d9fa4c76ba8611af9afa787d6422

Observation 63ed1e73-c172-4073-9638-5fc7fffd7ad0 · outbound

This paper cites an unresolved cited work.

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

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:45:30.438400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:18.159205Z digest=sha256:ed5c6761212f110fbe5e1134fca2f58e8f3c2f6bf46d33e6f924a7c24a210752

Observation 39a81028-6927-460e-99af-342227758c23 · outbound

This paper cites Collaborative Fairness in Federated Learning.

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

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:18.234824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:18.234824Z digest=sha256:ce14c19c76114035a9c1707c86231e7b0cd7fd63063c6382b00fc24cfd711c45

Observation c4171ffc-d3b6-4393-a760-e4768179a47a · outbound

This paper cites U.; Jeslin, J.

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

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:45:30.268256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:18.292338Z digest=sha256:037689f4de78867b46652a44641d8e2035adc1fcebf64d81360c40ba9b7784af

Observation b2ba7d95-968a-4f9a-886a-a778fa897fab · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:18.345055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:18.345055Z digest=sha256:bc8972fcf07299c20c142070b7675929227ff873a0d0172d745bb4664cf9c136

Observation cd634086-1ea7-41f9-88da-68f6a570c2c9 · outbound

This paper cites an unresolved cited work.

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

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:45:30.128051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:18.390936Z digest=sha256:946c455fe06026c25c0750987ec931f642f32d502b2b3719a97890a20aa8a6fb

Observation 18532188-6031-4676-9ae1-75a2551f5733 · outbound

This paper cites an unresolved cited work.

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

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:18.458332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:18.458332Z digest=sha256:c8310eff155cc5d09301b3c1d8256815e64b46b4cd2b25f2f1756879b6b88315

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.

source=arxiv_source observed=2026-08-07T13:45:18.504382Z digest=sha256:c0edac24ba194e5cb2a85166b00d146bf78c68cf8e8c8e4fc9aaedb3daee4d9a

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:18.547269Z digest=sha256:d1c94543d616bcd8ec76143b161eb8493e50f47aca850216ec338274ab659078

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.

source=arxiv_source observed=2026-08-07T13:45:18.621610Z digest=sha256:f1237accd7c911d2e30f35adae9f11c1b1c54303b1a5ef8e83d8753d84c5eeff

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:18.673553Z digest=sha256:c0373405b2976fe733b7d4254250d0b6ef404e9942990782f20d7fa020afcc82

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:18.737565Z digest=sha256:a1c5c2657b29bed1aa14263972d58f53051854dc23f818ed5c17e0f7758d3956

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:18.812713Z digest=sha256:bb8cdcfc15495bca8f1de5cfefb4833241eb1769df582b64d2b6635c92c5242f

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:18.862004Z digest=sha256:d5a42812d7024b431f7ba9fefe1f71e84bf078b5cfcc078c8a9db5e93c6e9cd3

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:18.916889Z digest=sha256:b968c3f3d2a829160d5255bd78d6f63d10ce3f2a00938aed423274e7067012ac

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:18.973118Z digest=sha256:797fe41b2e74fb9042243a41a93500b231a158c1a8cabfbcdb3857f451ae94c3

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.

source=arxiv_source observed=2026-08-07T13:45:19.025872Z digest=sha256:16c494099d0fb34de92585c58e9b7c65ed2fe0023511599ac5154a382144ecca

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:19.061304Z digest=sha256:abd961162a5811cd9fe8137eb56d8a292a63221595ca5518b6f0c2c5532d5bf5

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:19.144431Z digest=sha256:7d7dcee569be2a7e4ddcc37c4133b1b80624c8a1e94aefac4e537be1eab26fe6

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:19.209425Z digest=sha256:d772e59979b81304fb1bb25336889c5580b44b9c43af955f0eb8f424148a0086

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:19.260120Z digest=sha256:9d3a46c851854f8ca3ac1cc05c0a2d2b1eb59c2e2a2fbf3ae6cf992ed2dd1d69

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:19.300112Z digest=sha256:c2ab248a6b82dd31d1b6a6694dd2f368de224f0a81f3ba432b8f4ebacf57f544

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.

source=arxiv_source observed=2026-08-07T13:45:19.405215Z digest=sha256:68537d2b884ed7c5ff29e8fafd2375fa42cf3ca5a13028339ef9d289cf064d9e

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.

source=arxiv_source observed=2026-08-07T13:45:19.485853Z digest=sha256:92eb928adb7cb33522fb408416aa97394f4d1d4c76af54fb9da3a7c197ca1d23

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:19.561043Z digest=sha256:b5d79d40a00ece2d853e423cc1cbe4413d3907d54d2e4270d921c4c5b1b42e1a

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:19.661940Z digest=sha256:f60a37e238b8df13136d1b3c35bcc7372d7a30df66562fa2ed212992f5d58f0d

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:19.708280Z digest=sha256:92fff9654cb2a1bb16d951166b85ecd3c154360c40200499b884649d97982f7f

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.

source=arxiv_source observed=2026-08-07T13:45:19.787571Z digest=sha256:a1db0be2524151f07a9ab6c47d4d5a0854593c7ca60f4d511407ea08c0a91ad1

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:19.858176Z digest=sha256:af959eec15326820d38f99a725ddfedbc932bd821302d703b95d74e9b43766b6

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:19.918774Z digest=sha256:4c2089ffe94b246d0231a85c4f6a47d4ff4771e0d0064392599a2d7931547e4e

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.

source=arxiv_source observed=2026-08-07T13:45:19.977668Z digest=sha256:6674bf5d288a0d8896c75e7da35b209b1430f421af403aecdd99b3707c2159c0

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.043124Z digest=sha256:2380b3e607ff12518bd06cac1b0f4303c3ae2783783fa0b2c2de5d8a5070b2df

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.122227Z digest=sha256:3c971603c7a86fc28ad8c94356c32f3783853e24022104eccf20edfeb1e83681

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.220080Z digest=sha256:3b8f095e6d7ac3f773932c88b8c5d0c41005ad09087694d50ccdd4686aebf10c

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.275391Z digest=sha256:42a81fd3c2efb93c914d5466461eedc29f8619e309d0bb823a7204d300cb4c23

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.365615Z digest=sha256:79c6c4c2a71a0a05a389174f44a42a6672d7b80150beacef425e62f7fdbb6bbe

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.

source=arxiv_source observed=2026-08-07T13:45:20.458788Z digest=sha256:d319b51ca64994aac4dd5ce6fa3df8c29b6b28f9ba0280bcde89eaf4fdfdc7ac

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.546558Z digest=sha256:ff56b4f3a1f8c9174c9baf3ab19b91806ce7e4de75eb6c318a4c9018f918b37e

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.622060Z digest=sha256:afc4239315e1ff8dceb56f4f8d4eb987f858e3fca563ef5962171457e8a6f10c

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.703176Z digest=sha256:892444785b05cdaafa5c6aa0c4abe8f4473642b947266599046ca10c542f03e1

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.779996Z digest=sha256:12a20ef6edcf4539a595d0ceff2a5c0241c9e89b9e36c47c91623373793bf4a2

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.857829Z digest=sha256:057edd94c7a7befd8dd8b84a53c392aa9dba692500d2b694359497b0f3e92e8d

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.920349Z digest=sha256:1d5cedf71ea9306252626422ba900b226efa083ba131f992d150ae8d57742a40

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:20.988033Z digest=sha256:ce32bf218cfc8a23a99fdd074f0bca6c30d88b5dee3ac69b3be7231e67d60404

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T13:45:21.055413Z digest=sha256:47e6a0f1a9a4aa148f1e7344ef09dc5300204f1fb40a19a1be1af392931a2061

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.

source=arxiv_source observed=2026-08-07T13:45:21.109483Z digest=sha256:8274bb6473ba1d30c5947f6c4e4d67267d825fd0ebd140c60e11b113fd6299dc

Pith citing papers

No inbound Pith citation observations are available.