Paper Citation Record · LEDGER

FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2009.01974.

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

pith.paper-citation-record.v1
2009.01974 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:29:13.731146Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T13:33:28.498946Z

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 e685bfcb-bdb3-4404-ab09-7125d7ad36e3 · inbound

Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions cites this paper.

Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-23T23:48:39.251673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ee97bc4d-083c-4d7d-99aa-04129b35fa29 · inbound

Robust Knowledge Distillation in Federated Learning: Counteracting Backdoor Attacks cites this paper.

Robust Knowledge Distillation in Federated Learning: Counteracting Backdoor Attacks FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T18:29:13.731146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b732997-f368-44c4-8a4d-c5bdd9628862 · inbound

Federated Learning on Stochastic Neural Networks cites this paper.

Federated Learning on Stochastic Neural Networks FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T05:24:08.815038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b929656-90f8-4999-95d8-3a1911e7682c · inbound

FedMLAC: Mutual Learning Driven Heterogeneous Federated Audio Classification cites this paper.

FedMLAC: Mutual Learning Driven Heterogeneous Federated Audio Classification FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T04:38:10.176824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 873ff42b-9e81-43be-ac05-65ba20166b58 · inbound

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data cites this paper.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T22:59:37.136885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5d63ba5-4ea5-43ca-ab21-8bcbfe65faf5 · inbound

Towards Uncertainty-Aware Federated Granger Causal Learning cites this paper.

Towards Uncertainty-Aware Federated Granger Causal Learning FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:31:43.788344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2a9e9773-968c-4bc3-bc6a-65a9a5d63527 · inbound

Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learning cites this paper.

Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learning FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:13:21.247412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9ce52375-04ea-4780-8769-d28ca74b650f · inbound

FedQHD: Closed-Form Function-Space Federated Reinforcement Learning cites this paper.

FedQHD: Closed-Form Function-Space Federated Reinforcement Learning FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:33:28.500422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.