Paper Citation Record · LEDGER

Joint Graph Estimation and Signal Restoration for Robust Federated Learning

As of 21 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2505.11648.

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

pith.paper-citation-record.v1
2505.11648 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:00:34.838282Z

measured 32 of 32 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:00:34.738419Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T21:00:34.892602Z

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy24
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d4f486fb-6cc7-4f1c-a3ba-b202fae003eb · outbound

This paper cites Joint Graph Estimation and Signal Restoration for Robust Federated Learning.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Joint Graph Estimation and Signal Restoration for Robust Federated Learning

Reference 1

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Observation dd0d6a29-3dad-4d10-8278-4762c477ad20 · outbound

This paper cites We first briefly introduce the basic form of FL, then the GFL is reviewed.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning We first briefly introduce the basic form of FL, then the GFL is reviewed

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.168636Z

Source-reported events for the cited work

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Observation 203d4267-cd54-4e39-b36b-f64546e93283 · outbound

This paper cites First, we formalize the GFL framework.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning First, we formalize the GFL framework

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.158971Z

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Observation 675185db-e012-4d16-a4b3-94f1600e7a0b · outbound

This paper cites an unresolved cited work.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Unresolved cited work

Reference 4

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Observation 734fbdb4-8016-42da-8665-b002a7ecdd40 · outbound

This paper cites We first formulate a graph-based aggregation in the global model update as a DC optimization problem and then solve it using PDCA.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning We first formulate a graph-based aggregation in the global model update as a DC optimization problem and then solve it using PDCA

Reference 5

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Observation ffb6ec36-d9ff-4b11-adad-e23766aac836 · outbound

This paper cites an unresolved cited work.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:00:35.127970Z

Source-reported events for the cited work

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Observation 4b5636a9-b72c-485c-b340-375b38b02e68 · outbound

This paper cites First, we assume that the model param- eters, aggregated in the global model update, smoothly vary on the inter-client graph.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning First, we assume that the model param- eters, aggregated in the global model update, smoothly vary on the inter-client graph

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.117722Z

Source-reported events for the cited work

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Observation c0225f07-6f99-4958-8dbd-833100e0f9d7 · outbound

This paper cites Advances and open problems in federated learn- ing,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Advances and open problems in federated learn- ing,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.107158Z

Source-reported events for the cited work

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Observation 3e37d361-d534-4cce-b0e9-cd7380700945 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Communication-efficient learning of deep networks from decentralized data,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.097005Z

Source-reported events for the cited work

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Observation 0d912e42-2b0c-4fc2-86eb-abbcff8db21f · outbound

This paper cites Fed- erated learning for smart healthcare: A survey,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Fed- erated learning for smart healthcare: A survey,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.086206Z

Source-reported events for the cited work

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Observation 75ca7fc6-94ae-4aee-a834-f7dcffc2c37d · outbound

This paper cites Federated Learning: Opportunities and Challenges.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Federated Learning: Opportunities and Challenges

Reference 11

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Observation f6001c0f-3ca3-452f-84fb-d8256ef2a00a · outbound

This paper cites Robust federated learning with noisy communication,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Robust federated learning with noisy communication,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.077293Z

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 dffcfede-b651-4063-902a-7dbe300d8d64 · outbound

This paper cites Over- coming noisy and irrelevant data in federated learning,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Over- coming noisy and irrelevant data in federated learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.068098Z

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 81ec92ec-7f44-45bd-a0a6-d524c235b71d · outbound

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

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 14

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Observation 4a56ff54-4f2d-4eef-9c6b-7007192ef52b · outbound

This paper cites Personalized cross-silo federated learning on non- iid data,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Personalized cross-silo federated learning on non- iid data,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.057279Z

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 287dcc54-2507-4c61-b2c7-a8dee4d005f8 · outbound

This paper cites Personalized fed- erated learning with inferred collaboration graphs,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Personalized fed- erated learning with inferred collaboration graphs,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.047255Z

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 3ce08a35-0665-4433-a136-e8165b6ae453 · outbound

This paper cites An ef- ficient framework for clustered federated learning,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning An ef- ficient framework for clustered federated learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.037420Z

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 4242bd53-cc71-4f8a-a3c5-57a408817c32 · outbound

This paper cites The emerging field of signal processing on graphs: Extending high-dimensional data analysis to net- works and other irregular domains,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning The emerging field of signal processing on graphs: Extending high-dimensional data analysis to net- works and other irregular domains,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.026990Z

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 af18caa9-9143-4a20-94ae-6e24fbf53598 · outbound

This paper cites Dc formulations and algorithms for sparse optimization problems,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Dc formulations and algorithms for sparse optimization problems,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.013662Z

Source-reported events for the cited work

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Observation 3a312384-2068-43bc-9566-3a91c1a2dad1 · outbound

This paper cites Federated optimization in heterogeneous networks,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Federated optimization in heterogeneous networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:35.002594Z

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 bb4c0e3a-6f25-4c58-b78b-38ba0a1d17b4 · outbound

This paper cites SCAFFOLD: Stochastic controlled averag- ing for federated learning,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning SCAFFOLD: Stochastic controlled averag- ing for federated learning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:34.992572Z

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 01983b9c-81e1-4678-9aec-0eacd9d73309 · outbound

This paper cites Clustered federated learning: Model-agnostic distributed multitask optimization under privacy constraints,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Clustered federated learning: Model-agnostic distributed multitask optimization under privacy constraints,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:34.983141Z

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 16c33630-d894-488d-ad5b-644536d1c4d3 · outbound

This paper cites Federated Learning with Personalization Layers.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Federated Learning with Personalization Layers

Reference 23

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Source-reported events for the cited work

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Observation 74a7c48f-5119-4f00-ba10-ea06b1993191 · outbound

This paper cites Fed- erated multi-task learning,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Fed- erated multi-task learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:34.973009Z

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 1b682a75-1b74-4ee1-b0e8-3825064ce87f · outbound

This paper cites How to learn a graph from smooth signals,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning How to learn a graph from smooth signals,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:34.963785Z

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 c49c6e2e-358b-4100-a40e-71e31d194650 · outbound

This paper cites Convex optimization,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Convex optimization,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:34.953829Z

Source-reported events for the cited work

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Observation 724f12fd-ba6d-4e66-9f49-425663577775 · outbound

This paper cites Federated learning over wireless fading channels,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Federated learning over wireless fading channels,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:34.944822Z

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 3158c229-1121-4f8e-939b-3892190593fd · outbound

This paper cites Federated learning via over-the-air computation,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Federated learning via over-the-air computation,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T21:00:34.828974Z

Source-reported events for the cited work

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Observation 48dfdf0d-b2f6-4b6b-a789-d319548d29ab · outbound

This paper cites Gradient- based learning applied to document recognition,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Gradient- based learning applied to document recognition,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:34.929607Z

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 ce3cb1b4-d96f-4537-84f5-8dcfa6d480f7 · outbound

This paper cites Im- agenet classification with deep convolutional neural networks,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Im- agenet classification with deep convolutional neural networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:34.919208Z

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 19340d68-6b32-48d2-a0d8-ce66a5fba574 · outbound

This paper cites Learning laplacian matrix in smooth graph signal representa- tions,.

Joint Graph Estimation and Signal Restoration for Robust Federated Learning Learning laplacian matrix in smooth graph signal representa- tions,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:00:34.909176Z

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.

Pith citing papers

Observation d4f486fb-6cc7-4f1c-a3ba-b202fae003eb · inbound