Paper Citation Record · LEDGER

A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2504.21099.

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

pith.paper-citation-record.v1
2504.21099 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:48:46.467551Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T19:08:54.370557Z

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 972e8ed4-de66-4cc1-89a8-cfe5dd3865ad · 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 A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:32:16.622834Z

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 59f4c247-278a-4711-a3f6-5167c8c6ee46 · inbound

DP-FedLoRA: Privacy-Enhanced Federated Fine-Tuning for On-Device Large Language Models cites this paper.

DP-FedLoRA: Privacy-Enhanced Federated Fine-Tuning for On-Device Large Language Models A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T19:48:46.467551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 792fb8a8-d411-4a0c-9ada-55cab5fec6c2 · inbound

CoCo-Fed: A Unified Framework for Memory- and Communication-Efficient Federated Learning at the Wireless Edge cites this paper.

CoCo-Fed: A Unified Framework for Memory- and Communication-Efficient Federated Learning at the Wireless Edge A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T13:09:38.487561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39f13f13-52c3-4982-b7f6-6102d19d44ba · inbound

Beyond End-to-End: Dynamic Chain Optimization for Private LLM Adaptation on the Edge cites this paper.

Beyond End-to-End: Dynamic Chain Optimization for Private LLM Adaptation on the Edge A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:30:51.445573Z

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 cd70e0c6-056d-490d-a86e-0b8daa13a7c7 · inbound

UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models cites this paper.

UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:08:54.372572Z

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 9f8342d9-9c7b-475b-9bd3-5103ab37fa07 · inbound

FedCC: A Low-Resource Federated Adaptation of Foundation Models for Robust Corpus Callosum localization in Fetal Ultrasound Images cites this paper.

FedCC: A Low-Resource Federated Adaptation of Foundation Models for Robust Corpus Callosum localization in Fetal Ultrasound Images A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T09:26:23.455157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.