Paper Citation Record · LEDGER

On the Convergence of Local Descent Methods in Federated Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1910.14425.

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

pith.paper-citation-record.v1
1910.14425 v2

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 2026-08-08T06:32:00.761636+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:42:46.062575Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

170
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3fb4c442-8b3c-48e3-97fa-68224b76677b · inbound

DeCAF: Decentralized Consensus-And-Factorization for Low-Rank Adaptation of Foundation Models cites this paper.

DeCAF: Decentralized Consensus-And-Factorization for Low-Rank Adaptation of Foundation Models On the Convergence of Local Descent Methods in Federated Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:42:46.062575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f35827fd-fd0f-4179-8445-1cd5184a4a85 · inbound

Adaptive Federated LoRA in Heterogeneous Wireless Networks with Independent Sampling cites this paper.

Adaptive Federated LoRA in Heterogeneous Wireless Networks with Independent Sampling On the Convergence of Local Descent Methods in Federated Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T12:52:41.157026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26c6fc80-2ad1-4e19-b3cc-806255d538f9 · inbound

Strategies for Improving Communication Efficiency in Distributed and Federated Learning: Compression, Local Training, and Personalization cites this paper.

Strategies for Improving Communication Efficiency in Distributed and Federated Learning: Compression, Local Training, and Personalization On the Convergence of Local Descent Methods in Federated Learning

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-04T21:06:26.155651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b04997b-28b1-4868-aa45-25a18320db7b · inbound

ISAC for AI: A Trade-off Framework Across Data Acquisition and Transfer in Federated Learning cites this paper.

ISAC for AI: A Trade-off Framework Across Data Acquisition and Transfer in Federated Learning On the Convergence of Local Descent Methods in Federated Learning

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:22:18.970568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 37ddac67-f487-4368-81f5-643e0a28ae0c · inbound

Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity cites this paper.

Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity On the Convergence of Local Descent Methods in Federated Learning

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:32:50.921274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 83ff3c08-8beb-47d4-8487-3ea5fa2fc7e6 · inbound

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning cites this paper.

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning On the Convergence of Local Descent Methods in Federated Learning

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-20T08:03:08.757796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b7d22ddc-746a-4c5b-8899-6eba416e43bd · inbound

Federated Foundation Models Fine-Tuning with Heterogeneous Compressed Clients cites this paper.

Federated Foundation Models Fine-Tuning with Heterogeneous Compressed Clients On the Convergence of Local Descent Methods in Federated Learning

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T14:16:09.499421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.