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Paper Citation Record · LEDGER

Hierarchically Fair Federated Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2004.10386.

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

pith.paper-citation-record.v1
2004.10386 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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:58:04.002891Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T21:19:39.503670Z

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 e01b39bb-ff2b-4e81-8365-c608723581f0 · inbound

Distributed Quasi-Newton Method for Fair and Fast Federated Learning cites this paper.

Distributed Quasi-Newton Method for Fair and Fast Federated Learning Hierarchically Fair Federated Learning

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-10T18:58:04.002891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:58:04.002891Z digest=sha256:79624b7da7f08a6c5a7b75184b250b57c243147e520ea917092da4b3c8a4d90c

Observation fa797e2c-b888-464e-8a60-6770a61949c6 · inbound

Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks cites this paper.

Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks Hierarchically Fair Federated Learning

Reference 58

Resolution
verified exact
local_arxiv, observed 2026-08-08T21:19:39.510112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T21:19:39.441837Z digest=sha256:cb9713af7a268186ea933db35c8a15e3d62e7d4420ff55e0e0daae5a1b33cdae