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Paper Citation Record · LEDGER

Grounding Foundation Models through Federated Transfer Learning: A General Framework

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2311.17431.

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

pith.paper-citation-record.v1
2311.17431 v11

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:38:04.941422Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T15:34:57.605705Z

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 e0c94813-3b0a-47fd-aca0-d319f56a15f3 · inbound

A Survey on Foundation Models for Personalized Federated Intelligence cites this paper.

A Survey on Foundation Models for Personalized Federated Intelligence Grounding Foundation Models through Federated Transfer Learning: A General Framework

Reference 204

Resolution
verified exact
arxiv_id, observed 2026-05-22T15:34:57.607634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T15:32:15.293888Z digest=sha256:7567848a4eb3eaeda8ef794d8ee18237c8bfc1bb2797d8037fb7f149a89c4fa4

Observation cde9f457-f3c6-4b9f-b01c-c983ed71890a · inbound

Efficient Federated Learning with Heterogeneous Data and Adaptive Dropout cites this paper.

Efficient Federated Learning with Heterogeneous Data and Adaptive Dropout Grounding Foundation Models through Federated Transfer Learning: A General Framework

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T17:38:04.941422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:38:04.941422Z digest=sha256:6c5b1285e1e584ee9c97b4ddb6af308a0e7907a87873d3175449cd46810c3547

Observation 32bf6723-e0ed-42d3-9ff1-8e08ad54961a · inbound

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions cites this paper.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Grounding Foundation Models through Federated Transfer Learning: A General Framework

Reference 178

Resolution
unresolved
no resolver link, observed 2026-08-05T15:41:01.036971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:41:01.036971Z digest=sha256:d96e3d9cb4268c3d44e20c17c39d9b989535b7f78ec57bbde94c56c7a10bf997

Observation a40f95aa-e2ba-474c-8aeb-f84d13eb28cb · inbound

Foundational Models and Federated Learning: Survey, Taxonomy, Challenges and Practical Insights cites this paper.

Foundational Models and Federated Learning: Survey, Taxonomy, Challenges and Practical Insights Grounding Foundation Models through Federated Transfer Learning: A General Framework

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T05:37:33.433083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:37:33.433083Z digest=sha256:2d02ec01cc7375fe87ae5938a9019c602f8f335a889cb75701bb6dc31b1f2702