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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 7 inbound Pith citation observations for arXiv:2008.04489.

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

pith.paper-citation-record.v1
2008.04489 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:32:13.953341Z

measured 0 of 1 external citation measurements

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 ce188022-932f-4aeb-be9b-1a6484a0aab1 · inbound

On Learning Representations for Tabular Data Distillation cites this paper.

On Learning Representations for Tabular Data Distillation Federated Learning via Synthetic Data

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T15:32:13.953341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:32:13.953341Z digest=sha256:e4cbdbc06ece56464b07d6e3d9e565f2501345cca24e0b8cd98d9ba780ebebe3

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.

source=pdf_text observed=2026-08-09T06:02:19.116812Z digest=sha256:dfc7070faebc6912329b59a3a1d2eec7f9f9051128d2baefa0eaee2a1a53b9af

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.

source=pdf_text observed=2026-08-06T15:49:05.374401Z digest=sha256:c23ebb03eba785afbe7b14372e2ead3032edb6b1ec63c02ed3ab54de305cdd53

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.

source=pdf_text observed=2026-05-12T04:26:50.410397Z digest=sha256:fe87f1f46dac587587815ddbddcf383b070646fbb6683524cb36512b60111b53

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.

source=pdf_text observed=2026-05-20T22:21:03.637418Z digest=sha256:aab803994842c399584d9074bf8e0ce780359209b552db98e6d476e0048753e4

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.

source=pdf_text observed=2026-08-01T02:50:18.983562Z digest=sha256:ab662f456a88018ffdd1b896836617b92e1ef9927ca28f284328ff1c605388e8

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.

source=pdf_text observed=2026-08-03T01:50:46.986353Z digest=sha256:435fe41d17d6e117a5f4352c9084205a52b1e2da9756f251262bc87e6aeb697c