Paper Citation Record · LEDGER

Grounding Foundation Models through Federated Transfer Learning: A General Framework

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 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 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:31:21.792477Z

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 41bb3af0-c61e-4dfa-ba53-e649993a5354 · inbound

Protocol Learning, Decentralized Frontier Risk and the No-Off Problem cites this paper.

Protocol Learning, Decentralized Frontier Risk and the No-Off Problem Grounding Foundation Models through Federated Transfer Learning: A General Framework

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T18:31:21.792477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bd8efa3-77a7-4248-a341-3faef34e3153 · inbound

Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor cites this paper.

Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor Grounding Foundation Models through Federated Transfer Learning: A General Framework

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T04:49:47.273371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0fa5924-f71a-4383-8053-41854490c971 · inbound

DEFEND: A Large-scale 1M Dataset and Foundation Model for Tobacco Addiction Prevention cites this paper.

DEFEND: A Large-scale 1M Dataset and Foundation Model for Tobacco Addiction Prevention Grounding Foundation Models through Federated Transfer Learning: A General Framework

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T18:34:03.016862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-17T06:30:58.91139+00:00.

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.

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.

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.