Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Federated Learning via Synthetic Data
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2008.04489.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T06:02:19.116812Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T22:23:47.906851Z
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 b2f3a10a-a9d6-4015-b01d-c02076735a68 · inbound
E-3SFC: Communication-Efficient Federated Learning with Double-way Features Synthesizing cites this paper.
E-3SFC: Communication-Efficient Federated Learning with Double-way Features Synthesizing Federated Learning via Synthetic Data
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T06:02:19.116812Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1fbe9aa4-ca10-4390-897a-8c052ee07b45 · inbound
FedWCM: Unleashing the Potential of Momentum-based Federated Learning in Long-Tailed Scenarios cites this paper.
FedWCM: Unleashing the Potential of Momentum-based Federated Learning in Long-Tailed Scenarios Federated Learning via Synthetic Data
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:49:05.374401Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33372c80-7a07-40a0-b082-268ddacca4b8 · inbound
Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Federated Learning via Synthetic Data
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T06:16:27.558888Z
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.
Observation c87c9869-c8ab-47f6-b543-3fd6ad81ae65 · inbound
Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.
Concordia: Self-Improving Synthetic Tables for Federated LLMs Federated Learning via Synthetic Data
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:23:47.910624Z
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.
Observation a5242d1e-a088-4f5c-998a-93698f8ba5da · inbound
Dataset Distillation Based on Saliency-Driven Prototype Alignment cites this paper.
Dataset Distillation Based on Saliency-Driven Prototype Alignment Federated Learning via Synthetic Data
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T02:50:18.983562Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e197044d-868e-497c-9c52-be79ad3d4535 · inbound
Dataset Distillation Based on Saliency-Driven Prototype Alignment cites this paper.
Dataset Distillation Based on Saliency-Driven Prototype Alignment Federated Learning via Synthetic Data
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T01:50:46.986353Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.