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Paper Citation Record · LEDGER

FedCon: A Contrastive Framework for Federated Semi-Supervised Learning

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2109.04533.

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

pith.paper-citation-record.v1
2109.04533 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 2026-08-16T06:30:59.297886+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:42:26.829101Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:10:16.025912Z

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 8172724e-4678-4093-8439-e9b8274d2e50 · inbound

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things cites this paper.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things FedCon: A Contrastive Framework for Federated Semi-Supervised Learning

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:26.829101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:26.829101Z digest=sha256:d8dc23f621a8957aa3a24c6395083388c43bf9adc5ad1a7c91e9845ef424dbbc

Observation 8c59a844-e5c9-4211-976e-f68bb6e7b675 · inbound

Unified Alignment Protocol: Making Sense of the Unlabeled Data in New Domains cites this paper.

Unified Alignment Protocol: Making Sense of the Unlabeled Data in New Domains FedCon: A Contrastive Framework for Federated Semi-Supervised Learning

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T13:47:10.923740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:47:10.923740Z digest=sha256:328298b70516d64fc8476ce6d36ab63b470ff00ad1fb1bbf0732096a31ad22ac

Observation b491df6c-13e1-4440-be90-203d25465e98 · inbound

Semi-Supervised Federated Learning via Dual Contrastive Learning and Soft Labeling for Intelligent Fault Diagnosis cites this paper.

Semi-Supervised Federated Learning via Dual Contrastive Learning and Soft Labeling for Intelligent Fault Diagnosis FedCon: A Contrastive Framework for Federated Semi-Supervised Learning

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:10:16.116672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T18:10:14.991475Z digest=sha256:57a3ed56fd81d1e4b8a87dd03f179c92ee2f87b7159f69dbe69b204af3315131