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Paper Citation Record · LEDGER

Collaborative Fairness in Federated Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2008.12161.

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

pith.paper-citation-record.v1
2008.12161 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:45:18.234824Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

10
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

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

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

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=sha256:77f6f5552b6665ff558d3b784bff0e3f90313381caaefc98e72c07e00394729c

Observation dbad321e-4d0c-40be-89f3-1b8ee5126134 · inbound

Data-Free Client Contribution Estimation via Logit Maximization for Federated Learning cites this paper.

Data-Free Client Contribution Estimation via Logit Maximization for Federated Learning Collaborative Fairness in Federated Learning

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:53:19.646891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T13:52:09.660851Z digest=sha256:56f2f8ae8031c5065d525555783064feec30e46a823c3cf08de26080e8b64c65