Paper Citation Record · LEDGER

Mitigating Bias in Federated Learning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2012.02447.

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

pith.paper-citation-record.v1
2012.02447 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:57:46.406918Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T08:49:13.868410Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b458de11-afa7-4ec7-96eb-5eadba982bc0 · inbound

Incentivizing Honesty among Competitors in Collaborative Learning and Optimization cites this paper.

Incentivizing Honesty among Competitors in Collaborative Learning and Optimization Mitigating Bias in Federated Learning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-24T08:49:13.873290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1160cc2f-7550-4285-9820-769c8585602a · inbound

Incentivizing Truthful Collaboration in Heterogeneous Federated Learning cites this paper.

Incentivizing Truthful Collaboration in Heterogeneous Federated Learning Mitigating Bias in Federated Learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T04:57:46.406918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e716906-74e8-4e67-bb20-453d4b270091 · inbound

LEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks cites this paper.

LEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks Mitigating Bias in Federated Learning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-10T22:33:47.212591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08404cc6-3198-4185-8fd6-cd0a3a059451 · inbound

A Post-Processing-Based Fair Federated Learning Framework cites this paper.

A Post-Processing-Based Fair Federated Learning Framework Mitigating Bias in Federated Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T14:28:00.442687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Fairness in Federated Learning: Fairness for Whom? cites this paper.

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

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:11.863888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71b806e9-3406-4bd0-b627-c849cd55a559 · inbound

FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation cites this paper.

FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation Mitigating Bias in Federated Learning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-19T08:12:10.691769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 28146089-7b9a-4acf-b73c-9f90ac0e4fe3 · inbound

Fairness in Federated Learning: Trends, Challenges, and Opportunities cites this paper.

Fairness in Federated Learning: Trends, Challenges, and Opportunities Mitigating Bias in Federated Learning

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T13:16:20.377259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.