Paper Citation Record · LEDGER

A distillation-based approach integrating continual learning and federated learning for pervasive services

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2109.04197.

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

pith.paper-citation-record.v1
2109.04197 v1

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 2026-08-21T06:32:19.484+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:39:23.269495Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T09:15:44.195185Z

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 45d05268-b9b2-4043-8c82-a540e9d81809 · inbound

Federated Continual Learning for Edge-AI: A Comprehensive Survey cites this paper.

Federated Continual Learning for Edge-AI: A Comprehensive Survey A distillation-based approach integrating continual learning and federated learning for pervasive services

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T15:59:30.064161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 620df9f4-b103-43c0-a9d5-d40f2301998d · inbound

Federated Continual Learning: Concepts, Challenges, and Solutions cites this paper.

Federated Continual Learning: Concepts, Challenges, and Solutions A distillation-based approach integrating continual learning and federated learning for pervasive services

Reference 257

Resolution: unresolved; no resolver link, observed 2026-08-08T13:56:54.354719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7bddb1a-25e4-4145-b20e-d688fcf0a1d2 · inbound

TaskVAE: Task-Specific Variational Autoencoders for Exemplar Generation in Continual Learning for Human Activity Recognition cites this paper.

TaskVAE: Task-Specific Variational Autoencoders for Exemplar Generation in Continual Learning for Human Activity Recognition A distillation-based approach integrating continual learning and federated learning for pervasive services

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T22:39:23.269495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9ffe2ce-97af-4c8d-9964-6bf1682e8232 · inbound

Knowledge-Aware Evolution for Task-Free Streaming Federated Continual Learning with Arbitrary Class Overlap cites this paper.

Knowledge-Aware Evolution for Task-Free Streaming Federated Continual Learning with Arbitrary Class Overlap A distillation-based approach integrating continual learning and federated learning for pervasive services

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T07:36:56.321711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1038bce-04a8-4705-bd47-0e6bff05cf57 · inbound

Server-Proximal Aggregation for Federated Domain-Incremental Learning under Partial Participation: Task-Uniform Convergence and Backward Transfer cites this paper.

Server-Proximal Aggregation for Federated Domain-Incremental Learning under Partial Participation: Task-Uniform Convergence and Backward Transfer A distillation-based approach integrating continual learning and federated learning for pervasive services

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:21.691185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cd6948d-2e7d-47fb-95e9-59eb2af836d0 · inbound

FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection cites this paper.

FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection A distillation-based approach integrating continual learning and federated learning for pervasive services

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:46:17.949087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 64bc6375-b7b6-4676-a87c-d0c7b128450b · inbound

FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection cites this paper.

FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection A distillation-based approach integrating continual learning and federated learning for pervasive services

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:15:44.198715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.