Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2111.08211.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:50:19.699026Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T03:11:18.908292Z
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 f50c3980-3bb4-4687-b064-d185b9f7c57a · inbound
GeFL: Model-Agnostic Federated Learning with Generative Models cites this paper.
GeFL: Model-Agnostic Federated Learning with Generative Models FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T04:45:42.323389Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2f506d94-04bc-4170-9a89-4e5ba76114ce · inbound
GENE-FL: Gene-Driven Parameter-Efficient Dynamic Federated Learning cites this paper.
GENE-FL: Gene-Driven Parameter-Efficient Dynamic Federated Learning FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:50:19.699026Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4d1c7e3f-cd8a-4d03-8c1c-b8271c224d29 · inbound
FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data cites this paper.
FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:59:37.323613Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b3604f1e-245b-4e73-b9ff-5ffeec53e961 · 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 FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:52:40.666203Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d323fca7-e2f8-468c-880c-01bf2252962e · inbound
FedGMI: Generative Model-Driven Federated Learning for Probabilistic Mixture Inference cites this paper.
FedGMI: Generative Model-Driven Federated Learning for Probabilistic Mixture Inference FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T03:11:18.910398Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.