Paper Citation Record · LEDGER

When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2306.15546.

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

pith.paper-citation-record.v1
2306.15546 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 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 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:36:17.993928Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T15:34:57.812220Z

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 172c19ca-c4dc-4602-b3e9-fb15f0c73473 · inbound

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

A Survey on Foundation Models for Personalized Federated Intelligence When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-22T15:34:57.814391Z

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.

Observation fc76bdf5-91ef-4412-93ed-c57e1b8aedf4 · inbound

FedHL: Federated Learning for Heterogeneous Low-Rank Adaptation via Unbiased Aggregation cites this paper.

FedHL: Federated Learning for Heterogeneous Low-Rank Adaptation via Unbiased Aggregation When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:17.993928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2c01c79-c464-411d-9092-cef4b78746c8 · inbound

Assortment of Attention Heads: Accelerating Federated PEFT with Head Pruning and Strategic Client Selection cites this paper.

Assortment of Attention Heads: Accelerating Federated PEFT with Head Pruning and Strategic Client Selection When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:54.828295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33945407-5d97-4662-8645-ccb654ace330 · inbound

Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR cites this paper.

Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:48.331580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7c0a385-89d6-4c65-abe0-60a4fc34a601 · 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 When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:32:16.557022Z

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.

Observation 73dc3062-6bc7-4978-8d56-d9eafedb44fa · 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 When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:43.510839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2d94276-d50c-42b7-ae6e-c4e64d4208b9 · inbound

Towards Group Fairness with Multiple Sensitive Attributes in Federated Foundation Models cites this paper.

Towards Group Fairness with Multiple Sensitive Attributes in Federated Foundation Models When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T23:19:34.898298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8969388-64eb-45d1-8970-372af9273cd9 · inbound

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

FedPhD: Federated Pruning with Hierarchical Learning of Diffusion Models When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T19:11:22.712277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b71659f-a181-45cc-a244-55cfe7fcd25c · inbound

Scaling Decentralized Learning with FLock cites this paper.

Scaling Decentralized Learning with FLock When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T15:40:19.442782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d1eb8ec-e472-480c-a81f-4e09d1b8ee0a · inbound

Flexible Personalized Split Federated Learning for On-Device Fine-Tuning of Foundation Models cites this paper.

Flexible Personalized Split Federated Learning for On-Device Fine-Tuning of Foundation Models When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T20:33:20.448378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe2a3f46-fee7-4188-9920-2bbbe1a0923b · inbound

BetaWeb: Towards a Blockchain-enabled Trustworthy Agentic Web cites this paper.

BetaWeb: Towards a Blockchain-enabled Trustworthy Agentic Web When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 116

Resolution: unresolved; no resolver link, observed 2026-08-05T18:55:33.803081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62669d8c-1e79-41d5-b5ee-343ad64e9cf0 · inbound

FEDEXCHANGE: Bridging the Domain Gap in Federated Object Detection for Free cites this paper.

FEDEXCHANGE: Bridging the Domain Gap in Federated Object Detection for Free When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-05T12:23:54.359683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd755cb6-de30-443e-9d19-c2f544c15639 · inbound

Task-Centric Personalized Federated Fine-Tuning of Language Models cites this paper.

Task-Centric Personalized Federated Fine-Tuning of Language Models When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:27:59.627493Z

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.

Observation 4a410fe2-a495-4ed6-b6e5-ffb54e75af45 · inbound

FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training cites this paper.

FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:31:08.752069Z

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.

Observation 744239e0-fd3e-4bbb-9dc5-de02421523fa · inbound

FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training cites this paper.

FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:11:25.490040Z

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.

Observation 5bbeda74-911f-4c9e-9083-edffce5f87dc · inbound

FM$^2$: Unified Federated Foundation Models for Heterogeneous Multimodal Medical Imaging cites this paper.

FM$^2$: Unified Federated Foundation Models for Heterogeneous Multimodal Medical Imaging When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-02T05:28:45.032058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.