Paper Citation Record · LEDGER

Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2204.13399.

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

pith.paper-citation-record.v1
2204.13399 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:59:37.289056Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:57:30.737974Z

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 8a3b456f-ceb6-4f39-aa00-85d8714e8fb1 · 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 Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T22:59:37.289056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fafefb3-408f-4859-b33c-24b4ab9d8269 · inbound

FedWCM: Unleashing the Potential of Momentum-based Federated Learning in Long-Tailed Scenarios cites this paper.

FedWCM: Unleashing the Potential of Momentum-based Federated Learning in Long-Tailed Scenarios Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T15:49:08.632443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dac63b86-134e-45ea-8be8-64cba28fa897 · inbound

Multi-Level Analyzation of Imbalance to Resolve Non-IID-Ness in Federated Learning cites this paper.

Multi-Level Analyzation of Imbalance to Resolve Non-IID-Ness in Federated Learning Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:57:30.739841Z

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 ff5fffaf-c30d-438f-afb3-4c1ad907bff6 · inbound

Condensing Large-Scale Datasets Directly with Minimal Information Loss cites this paper.

Condensing Large-Scale Datasets Directly with Minimal Information Loss Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-02T14:07:02.387995Z

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.