Paper Citation Record · LEDGER

Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2305.11414.

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

pith.paper-citation-record.v1
2305.11414 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:53:06.637278Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:16:58.676882Z

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 e3ee4d4f-c413-46e7-8b5a-0d3671904afc · inbound

F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics cites this paper.

F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-12T18:53:06.637278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ddf171c-32ae-4fe0-9c4a-fd9f7dad1817 · inbound

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

Protocol Learning, Decentralized Frontier Risk and the No-Off Problem Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-11T18:31:21.983485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88773e93-f613-4294-a37a-761c51d12918 · inbound

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning cites this paper.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.392209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92105706-3b0b-431f-8311-d51b0fe52308 · inbound

Multifaceted User Modeling in Recommendation: A Federated Foundation Models Approach cites this paper.

Multifaceted User Modeling in Recommendation: A Federated Foundation Models Approach Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T05:59:18.755231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0c1be88-c442-47d7-a53f-5fa822d7fe47 · inbound

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things cites this paper.

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:14:51.846056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 934185bd-3d28-44e4-902e-bf3e1b2110da · inbound

A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation cites this paper.

A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:32:16.628423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a78a566f-48b2-4eb5-842a-fd1e75ccb2a9 · inbound

Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation cites this paper.

Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:42.293293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6882a275-b96b-492a-b12e-99218086745b · inbound

Personalized Federated Learning via Dual-Prompt Optimization and Cross Fusion cites this paper.

Personalized Federated Learning via Dual-Prompt Optimization and Cross Fusion Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T22:36:47.680139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8b1a959-0fe6-46db-9c69-61dc585d99d3 · inbound

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models cites this paper.

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T19:11:23.069302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23075fa4-7062-43f8-9dc3-f1fb3956993c · inbound

Amortizing Federated Adaptation: Hypernetwork Driven LoRA for Personalized Foundation Models cites this paper.

Amortizing Federated Adaptation: Hypernetwork Driven LoRA for Personalized Foundation Models Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-07-02T13:16:58.678629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.