Paper Citation Record · LEDGER

Rethinking Federated Graph Learning: A Data Condensation Perspective

As of 16 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2505.02573.

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

pith.paper-citation-record.v1
2505.02573 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:53:19.566754Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:47:53.386974Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T18:47:53.570459Z

Reference resolution

32 of 32 outbound references displayed

verified exact0
verified fuzzy17
unresolved15
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 904831ad-4ba5-481e-afa8-8461af581ff2 · outbound

This paper cites Optuna: A next-generation hyperparameter optimization framework.

Rethinking Federated Graph Learning: A Data Condensation Perspective Optuna: A next-generation hyperparameter optimization framework

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.920138Z

Source-reported events for the cited work

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Observation aa84409e-65ad-4983-b761-1a9b52d008d0 · outbound

This paper cites Skipgnn: pre- dicting molecular interactions with skip-graph networks.

Rethinking Federated Graph Learning: A Data Condensation Perspective Skipgnn: pre- dicting molecular interactions with skip-graph networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.855446Z

Source-reported events for the cited work

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Observation 915a5110-d9e4-49ba-8a38-1ac119023799 · outbound

This paper cites Graph Condensation for Graph Neural Networks.

Rethinking Federated Graph Learning: A Data Condensation Perspective Graph Condensation for Graph Neural Networks

Reference 8

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Observation 149f4319-9bfa-4c97-a497-a7cd41bb649b · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learning.

Rethinking Federated Graph Learning: A Data Condensation Perspective Scaffold: Stochastic controlled averaging for federated learning

Reference 10

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Source-reported events for the cited work

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Observation 70720830-eca5-4c9e-9205-5d473f51e573 · outbound

This paper cites Federated optimization in heterogeneous networks.

Rethinking Federated Graph Learning: A Data Condensation Perspective Federated optimization in heterogeneous networks

Reference 13

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Observation 1149ad37-1171-4777-924c-a154c5d1ba7f · outbound

This paper cites Model-contrastive federated learning.

Rethinking Federated Graph Learning: A Data Condensation Perspective Model-contrastive federated learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.822121Z

Source-reported events for the cited work

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Observation 2c6bb4c3-9d1b-4f0b-b342-2ad560adcd79 · outbound

This paper cites Federated learning on non-iid data silos: An experimental study.

Rethinking Federated Graph Learning: A Data Condensation Perspective Federated learning on non-iid data silos: An experimental study

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.810111Z

Source-reported events for the cited work

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Observation 71e4586a-fa09-4142-908d-65851ba68e15 · outbound

This paper cites AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity.

Rethinking Federated Graph Learning: A Data Condensation Perspective AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity

Reference 16

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Observation e3a3e4aa-dd9d-490b-8e7f-df6aad460374 · outbound

This paper cites Feder- ated learning in mobile edge networks: A comprehen- sive survey.

Rethinking Federated Graph Learning: A Data Condensation Perspective Feder- ated learning in mobile edge networks: A comprehen- sive survey

Reference 18

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Observation b04db275-6aec-400b-bfe6-4412e3d2322a · outbound

This paper cites Revisiting heterophily for graph neural networks.

Rethinking Federated Graph Learning: A Data Condensation Perspective Revisiting heterophily for graph neural networks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.790637Z

Source-reported events for the cited work

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Observation e17e8c0a-d6b3-4e47-b411-f6029ef5c74f · outbound

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

Rethinking Federated Graph Learning: A Data Condensation Perspective Communication-efficient learning of deep networks from decentralized data

Reference 20

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Source-reported events for the cited work

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Observation 49b21d18-7654-4318-9b37-8c5ed61ba759 · outbound

This paper cites Rethinking architecture design for tack- ling data heterogeneity in federated learning.

Rethinking Federated Graph Learning: A Data Condensation Perspective Rethinking architecture design for tack- ling data heterogeneity in federated learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.760952Z

Source-reported events for the cited work

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Observation 85bd73ad-b2e2-4cbb-a7e0-abbe6f838853 · outbound

This paper cites Pitfalls of Graph Neural Network Evaluation.

Rethinking Federated Graph Learning: A Data Condensation Perspective Pitfalls of Graph Neural Network Evaluation

Reference 23

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Observation 65dcd08c-84bb-4dd1-a491-11a569ca58c2 · outbound

This paper cites Social influence analysis in large-scale networks.

Rethinking Federated Graph Learning: A Data Condensation Perspective Social influence analysis in large-scale networks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.741947Z

Source-reported events for the cited work

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Observation 1a67ab2d-496d-4d0e-91ae-d02063d37c8b · outbound

This paper cites Graphgan: Graph representation learning with generative adversarial nets.

Rethinking Federated Graph Learning: A Data Condensation Perspective Graphgan: Graph representation learning with generative adversarial nets

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.716636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3611b82c-2a13-4d0f-8a93-00a946ead1df · outbound

This paper cites FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation.

Rethinking Federated Graph Learning: A Data Condensation Perspective FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation

Reference 28

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Observation 8f5a8e44-8fdc-46fd-810b-d6f9ac8f6982 · outbound

This paper cites Graph convolutional networks: a comprehensive review.

Rethinking Federated Graph Learning: A Data Condensation Perspective Graph convolutional networks: a comprehensive review

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.705478Z

Source-reported events for the cited work

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Observation ea0bc703-7ffc-4db6-b879-61a2f185f61c · outbound

This paper cites Subgraph federated learn- ing with missing neighbor generation.

Rethinking Federated Graph Learning: A Data Condensation Perspective Subgraph federated learn- ing with missing neighbor generation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.693621Z

Source-reported events for the cited work

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Observation bdcf7673-c344-4f1c-81ef-c8979d0506fa · outbound

This paper cites Dataset Condensation with Gradient Matching.

Rethinking Federated Graph Learning: A Data Condensation Perspective Dataset Condensation with Gradient Matching

Reference 31

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Source-reported events for the cited work

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Observation 5d043490-d38e-4965-9727-2677eff8fdf4 · outbound

This paper cites Rossi, Anup Rao, Tung Mai, Nedim Lipka, Nesreen K.

Rethinking Federated Graph Learning: A Data Condensation Perspective Rossi, Anup Rao, Tung Mai, Nedim Lipka, Nesreen K

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.681441Z

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Observation 8b8dd76a-00b7-4051-bac7-fcdf3035ac61 · outbound

This paper cites FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning.

Rethinking Federated Graph Learning: A Data Condensation Perspective FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning

Reference 33

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Observation 5e4c9c1f-832b-46ab-9dd6-c5293ab109ce · outbound

This paper cites Privacy for free: How does dataset condensation help pri- vacy? In International Conference on Machine Learning, pages 5378–5396.

Rethinking Federated Graph Learning: A Data Condensation Perspective Privacy for free: How does dataset condensation help pri- vacy? In International Conference on Machine Learning, pages 5378–5396

Reference 2008

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.878468Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 968dc280-a134-44ad-91fe-ac44a2ac13c1 · outbound

This paper cites [V oigt and V on dem Bussche, 2017] Paul V oigt and Axel V on dem Bussche.

Rethinking Federated Graph Learning: A Data Condensation Perspective [V oigt and V on dem Bussche, 2017] Paul V oigt and Axel V on dem Bussche

Reference 2009

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.729051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7a1ed16f-91e9-4ce7-80be-3b4b13f8da87 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Rethinking Federated Graph Learning: A Data Condensation Perspective Semi-Supervised Classification with Graph Convolutional Networks

Reference 2016

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Observation c9c0d726-b85e-4674-81d4-b6f7421bf480 · outbound

This paper cites A critical look at evaluation of gnns under heterophily: Are we really making progress? In The Eleventh International Conference on Learning Representations,.

Rethinking Federated Graph Learning: A Data Condensation Perspective A critical look at evaluation of gnns under heterophily: Are we really making progress? In The Eleventh International Conference on Learning Representations,

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.772762Z

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Observation 7e76b35e-2687-4556-866d-cdea90804290 · outbound

This paper cites Graphvae: Towards generation of small graphs using variational autoencoders.

Rethinking Federated Graph Learning: A Data Condensation Perspective Graphvae: Towards generation of small graphs using variational autoencoders

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-16T00:53:19.531841Z

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Observation 2aeb4cf8-3a42-4a93-9bd8-5a8e612d39d1 · outbound

This paper cites Personalized sub- graph federated learning.

Rethinking Federated Graph Learning: A Data Condensation Perspective Personalized sub- graph federated learning

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.908645Z

Source-reported events for the cited work

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Observation d8f7e363-3e43-4922-ac98-b152b924cbf3 · outbound

This paper cites Fast unfolding of communities in large networks.

Rethinking Federated Graph Learning: A Data Condensation Perspective Fast unfolding of communities in large networks

Reference 2020

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Observation 39ee76c4-48dd-49d6-9cef-db662d8b5c05 · outbound

This paper cites Condensing graphs via one-step gradient matching.

Rethinking Federated Graph Learning: A Data Condensation Perspective Condensing graphs via one-step gradient matching

Reference 2021

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Observation c6ac7f1a-4b47-4825-87e2-54e9f14dc57e · outbound

This paper cites Federated graph machine learning: A survey of concepts, techniques, and applica- tions.

Rethinking Federated Graph Learning: A Data Condensation Perspective Federated graph machine learning: A survey of concepts, techniques, and applica- tions

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.866647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d467d9e7-4a82-4e8c-a7d1-f4dbabddd436 · outbound

This paper cites The challenges of modeling and forecasting the spread of covid-19.

Rethinking Federated Graph Learning: A Data Condensation Perspective The challenges of modeling and forecasting the spread of covid-19

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:53:19.896354Z

Source-reported events for the cited work

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Observation 119590b9-2146-4091-b2e0-63033c5d7e1b · outbound

This paper cites FedGTA: Topology-aware Averaging for Federated Graph Learning.

Rethinking Federated Graph Learning: A Data Condensation Perspective FedGTA: Topology-aware Averaging for Federated Graph Learning

Reference 2024

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Pith citing papers

Observation fc0cbd24-94fe-40d9-a855-cefb87d130e3 · inbound

Personalized One-shot Federated Graph Learning for Heterogeneous Clients cites this paper.

Personalized One-shot Federated Graph Learning for Heterogeneous Clients Rethinking Federated Graph Learning: A Data Condensation Perspective

Reference 66

Resolution: verified exact; local_arxiv, observed 2026-08-12T18:47:53.578151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.