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Paper Citation Record · LEDGER

Model Pruning Enables Efficient Federated Learning on Edge Devices

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1909.12326.

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

pith.paper-citation-record.v1
1909.12326 v5

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:49:41.788918Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:49:42.447819Z

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 37e28ecf-0e49-4800-b868-591277d83950 · inbound

Efficient Federated Learning with Encrypted Data Sharing for Data-Heterogeneous Edge Devices cites this paper.

Efficient Federated Learning with Encrypted Data Sharing for Data-Heterogeneous Edge Devices Model Pruning Enables Efficient Federated Learning on Edge Devices

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:49:42.452511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:49:41.788918Z digest=sha256:1fb6cbb61045df798af1572bd1ff8159daa0990f6136a7daf35c6dc654e6cf5d

Observation 75bdbc8d-5fbd-4b6f-81d9-8dab48fa55c4 · inbound

FedBiF: Communication-Efficient Federated Learning via Bits Freezing cites this paper.

FedBiF: Communication-Efficient Federated Learning via Bits Freezing Model Pruning Enables Efficient Federated Learning on Edge Devices

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-04T18:10:17.740703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:10:17.740703Z digest=sha256:1b6809c1ce439332ecb51bab0c7ef8479d09a732f75b655ca955bf747dabf153