Pith. sign in

Paper Citation Record · LEDGER

FedCM: Federated Learning with Client-level Momentum

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2106.10874.

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

pith.paper-citation-record.v1
2106.10874 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:25:58.192857Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T05:51:26.596507Z

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 f861f45f-d96e-4dc5-b911-505a5563a0fc · inbound

Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning cites this paper.

Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning FedCM: Federated Learning with Client-level Momentum

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T13:25:58.192857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:25:58.192857Z digest=sha256:9d540c3cb92efafa07e806a160d56f290b0d677cf751a3d576503c5b0d254966

Observation 9bca6165-de15-4254-8872-93d48e48beb6 · inbound

pFedSOP : Accelerating Training Of Personalized Federated Learning Using Second-Order Optimization cites this paper.

pFedSOP : Accelerating Training Of Personalized Federated Learning Using Second-Order Optimization FedCM: Federated Learning with Client-level Momentum

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T05:46:25.018730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:46:25.018730Z digest=sha256:cfa39f07a2d4cd2921e16e3d8ddc170db40db5e6c18e23a251c79fe8b6b929f3

Observation 46d7137f-f743-4f76-b653-a68c78b947fd · inbound

FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization cites this paper.

FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization FedCM: Federated Learning with Client-level Momentum

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T21:47:46.037637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:47:46.037637Z digest=sha256:2a4c6af0534f4c5296c9e5f72b5a1aa242c7e0e53c89719c6d2cece24d40f825

Observation 9135b52f-df57-44b4-8531-ae06cdf0c97f · 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 FedCM: Federated Learning with Client-level Momentum

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T15:49:10.143258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:49:10.143258Z digest=sha256:e2ec35fec426f8b91f2243506c7da2980fbfa5efe7568e792ec7ffd1c6928d1f

Observation 9512fa90-b500-4de3-a0b0-c3e629664bbe · inbound

Generalizable Federated Learning using Client Adaptive Focal Modulation cites this paper.

Generalizable Federated Learning using Client Adaptive Focal Modulation FedCM: Federated Learning with Client-level Momentum

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-05T20:19:10.998252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:19:10.998252Z digest=sha256:dd4a07f8176b36523e6b6fa6a61e6f0fa49f9c547b039abaa89c97ac7e323743

Observation cd0b8d07-85f4-43fc-b439-2014d2980b6e · 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 FedCM: Federated Learning with Client-level Momentum

Reference 223

Resolution
unresolved
no resolver link, observed 2026-08-04T21:06:26.577174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T21:06:26.577174Z digest=sha256:d50f903a402f851ea6a3fee428b85cbb68f9b15b9906493ef05c6f6024bc8d42

Observation 88d9047a-2d62-46d7-8cc4-198ea48bebbd · inbound

Rethinking the Personalized Relaxed Initialization in the Federated Learning: Consistency and Generalization cites this paper.

Rethinking the Personalized Relaxed Initialization in the Federated Learning: Consistency and Generalization FedCM: Federated Learning with Client-level Momentum

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:00:59.540717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T16:20:43.523895Z digest=sha256:fd3d14995623aba5f096ffac20563d611f1e6f2fee353a39087ada8aa6a024ac

Observation dc6bf277-292b-4369-be85-5ddd69a20bc7 · inbound

FedVSSAM: Mitigating Flatness Incompatibility in Sharpness-Aware Federated Learning cites this paper.

FedVSSAM: Mitigating Flatness Incompatibility in Sharpness-Aware Federated Learning FedCM: Federated Learning with Client-level Momentum

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:51:26.601729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T04:51:33.265354Z digest=sha256:3b82a806df94dafb38e14dc39e9fbce1f997269fcd1e3a0a52da6317cba777d4

Observation 13202aaa-e7b6-4a4f-91d2-ab361166a7f1 · inbound

FedACT: Federated Adaptive Coordinate Trust Modulation for Robust Transformer Training under Data Heterogeneity cites this paper.

FedACT: Federated Adaptive Coordinate Trust Modulation for Robust Transformer Training under Data Heterogeneity FedCM: Federated Learning with Client-level Momentum

Reference 68

Resolution
unresolved
no resolver link, observed 2026-07-12T00:07:55.485589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T00:07:55.485589Z digest=sha256:0679f3ca492d7d16506440fa0fe20a3673ef6bcee66cbaa002a9ed8cada578fb

Observation 598366a7-942e-46c5-bf09-9ab64a05aa81 · inbound

FedFFT: Taming Client Drift in Federated SAM via Spectral Perturbation Filtering cites this paper.

FedFFT: Taming Client Drift in Federated SAM via Spectral Perturbation Filtering FedCM: Federated Learning with Client-level Momentum

Reference 14

Resolution
unresolved
no resolver link, observed 2026-07-11T21:13:04.339445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:13:04.339445Z digest=sha256:c70fe17d4346c4a47e2b6b5fdcaede952e68e0f2ccabb0316a60fd4630eb58d5

Observation e505bb3d-250f-47fa-ba0e-4573de93ba44 · inbound

SpecGradFilter: A Spectral Gradient Filtering Framework for Taming Federated Heterogeneity cites this paper.

SpecGradFilter: A Spectral Gradient Filtering Framework for Taming Federated Heterogeneity FedCM: Federated Learning with Client-level Momentum

Reference 34

Resolution
unresolved
no resolver link, observed 2026-07-11T21:05:03.994941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:05:03.994941Z digest=sha256:dac962361da7358afcfe0a765743596ad785ed4631012cbffa9739c6c3780d04