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Paper Citation Record · LEDGER

Federated Knowledge Distillation

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2011.02367.

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

pith.paper-citation-record.v1
2011.02367 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:48:16.358797Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:52:41.806805Z

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 7d3881c8-314d-46d2-8b65-41004354985c · inbound

GeFL: Model-Agnostic Federated Learning with Generative Models cites this paper.

GeFL: Model-Agnostic Federated Learning with Generative Models Federated Knowledge Distillation

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:42.290440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T04:45:42.290440Z digest=sha256:2079a283ab014b3f216c1b4225430099c61fafa3e58a5a9e52534957dd190e24

Observation b5cc40c8-0e78-45fa-a067-d0e588a08ac7 · inbound

Learning Critically: Selective Self Distillation in Federated Learning on Non-IID Data cites this paper.

Learning Critically: Selective Self Distillation in Federated Learning on Non-IID Data Federated Knowledge Distillation

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-16T11:48:16.358797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:48:16.358797Z digest=sha256:1caad7fa91c5d37f585ab0c1d1ffb94aadac59813db105395eea1044c5f6ad9f

Observation d3fe519b-08b5-401e-ac27-8fcbd8ab411e · inbound

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation cites this paper.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Federated Knowledge Distillation

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:52:41.898944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T22:52:40.184500Z digest=sha256:fb51fa4591f590b9a260c0e433b3fe9bace9bae64f56308b84c777c0fce77ddc