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Paper Citation Record · LEDGER

FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning

As of 13 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 1 inbound Pith citation observation for arXiv:2412.14226.

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

pith.paper-citation-record.v1
2412.14226 v2

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:37:05.965566Z

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T15:16:58.221358Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T10:51:20.668261Z

Reference resolution

7 of 7 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 44dc1402-96b2-4eae-91b5-75f303086c3b · outbound

This paper cites Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning.

FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-11T12:37:06.280042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T12:37:05.921408Z digest=sha256:c065ccb2a129e80d55b56c63753b5f23c1e11447bf8315b817952a3516ec92e9

Observation 7d539e8b-c598-4786-bd8e-464da385a314 · outbound

This paper cites FedSTS : A Stratified Client Selection Framework for Consistently Fast Federated Learning.

FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning FedSTS : A Stratified Client Selection Framework for Consistently Fast Federated Learning

Reference 2

Resolution
metadata mismatch
raw_fallback, observed 2026-08-11T12:37:06.252816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T12:37:05.933102Z digest=sha256:cae8766af1724bbb07bf162f32ca1423ac0233ca466b43c6f581f5dc9c7c3c7e

Observation c7e2187b-de8d-4e29-b7d8-69bad74c45cd · outbound

This paper cites Federated Optimization in Heterogeneous Networks.

FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning Federated Optimization in Heterogeneous Networks

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T12:37:05.938687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:37:05.938687Z digest=sha256:c2a8c032cbce55ce0508cbc9c3ea9253aaee904fc3522a352d8b8b1c94895e04

Observation d8d3d955-af38-4699-8c83-69cd73e535ef · outbound

This paper cites Federated learning based on stratified sampling and regularization.

FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning Federated learning based on stratified sampling and regularization

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T12:37:05.944966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:37:05.944966Z digest=sha256:0e6455c9c8471871f9b1c56c44f4f4891987209929c8713916fc478896c35f25

Observation dc8b8636-59e2-45b0-b97f-7982dc788bab · outbound

This paper cites Communication-Efficient Learning of Deep Networks from Decentralized Data.

FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-11T12:37:05.952679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:37:05.952679Z digest=sha256:16f75f6489302b0de26de430483974228304c50cc3ff7a797ee75c8d9052d461

Observation 9eaf7a5a-313c-4e30-8171-187c8685bfd0 · outbound

This paper cites FedSampling: A Better Sampling Strategy for Federated Learning.

FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning FedSampling: A Better Sampling Strategy for Federated Learning

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-11T12:37:06.032962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T12:37:05.958345Z digest=sha256:6f4a5cbf4d4ff42df6b020132a83f88ad36b86d82fe3428f56d5dcd3d92743be

Observation 9614c17c-f3f5-478a-bc28-194d055e9b75 · outbound

This paper cites write newline.

FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning write newline

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T12:37:05.965566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:37:05.965566Z digest=sha256:787d11093efe382a17f98882f017191af53755a60b8d94a5ddf98a6ef1c15492

Pith citing papers

Observation 96be0276-8ca7-46f4-9188-b74b04d7888e · inbound

Evolution of Optimization Methods: Algorithms, Scenarios, and Evaluations cites this paper.

Evolution of Optimization Methods: Algorithms, Scenarios, and Evaluations FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:51:20.716009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-10T15:16:58.221358Z digest=sha256:be60eed2038bf15dbe74a2169499c7269f29b00f7db443d66ab90f7014b7e02e