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Paper Citation Record · LEDGER

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks

As of 11 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2412.16144.

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

pith.paper-citation-record.v1
2412.16144 v1

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:51:16.308913Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

60 of 60 outbound references displayed

  • verified exact8
  • verified fuzzy3
  • unresolved49
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f4f20dc9-d7c6-4e19-adde-407d72b47b8c · outbound

This paper cites , " * write output.state after.block = add.period write newline.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks , " * write output.state after.block = add.period write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.089312Z digest=sha256:e08924d7ca813da47f08795ad4bf31be4d7ad832c3bc41633107a885ab244b63

Observation f86659fd-c101-4ae1-9edc-416ba7cf83a1 · outbound

This paper cites write newline.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks write newline

Reference 2

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source=arxiv_source observed=2026-08-11T10:51:16.095011Z digest=sha256:0b88ea64c755033ed8f3c913d39855cf05681d29b8b3906fd2b0563e25fbb6d1

Observation 9f7145f7-9908-4fed-af52-3e02bf92199b · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.098984Z digest=sha256:d4c70a2f105213f540e0702ff2884b1cb3c08b9b5210d4693183118967872f5b

Observation 57f807e3-e4ef-4ed9-90a5-66a7ff9aaa95 · outbound

This paper cites B.; Patel, S.; Ramage, D.; Segal, A.; and Seth, K.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks B.; Patel, S.; Ramage, D.; Segal, A.; and Seth, K

Reference 4

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raw_fallback, observed 2026-08-11T10:51:16.918815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.102412Z digest=sha256:a6cac230db42edc884cbc3b8e3308a4aa782f5988db9013c0f481d37903d118f

Observation cb0d2c39-3820-499a-9531-9c19c2b9cc34 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.105884Z digest=sha256:22cacafceb7232dd5ff71edcc851ab16ca0b432c64a796d63d3a0b9c1cc0e24a

Observation a0e440e7-ad0d-45d1-b635-922e5252dce1 · outbound

This paper cites How Attentive are Graph Attention Networks?.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks How Attentive are Graph Attention Networks?

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.109470Z digest=sha256:6613657876eadc821c7a57a71e8950dfea7a2756b100f18daa1fdd6c2de14588

Observation 6b68cd74-0626-4360-a51e-64bfea8a4a69 · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 7

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-11T10:51:16.113665Z digest=sha256:cd2d8d7b352a68b3ec224e80bad5d8c319a6717309696382cd7b4c4bf9db8f53

Observation 8ed86c85-88ad-4a0e-8e04-6ceb7d4d10f9 · outbound

This paper cites M.; Bruna, J.; LeCun, Y.; Szlam, A.; and Vandergheynst, P.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks M.; Bruna, J.; LeCun, Y.; Szlam, A.; and Vandergheynst, P

Reference 8

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raw_fallback, observed 2026-08-11T10:51:16.899836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.117584Z digest=sha256:383c83f63cfddb9a01127922d39fd1dd9bbaa603945fe2397fe1cab1534c4857

Observation 1c29477f-2d31-4394-a460-4555c2f1735d · outbound

This paper cites FedGL: Federated Graph Learning Framework with Global Self-Supervision.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks FedGL: Federated Graph Learning Framework with Global Self-Supervision

Reference 9

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source=arxiv_source observed=2026-08-11T10:51:16.121285Z digest=sha256:f0fed298ec93c96173b2d09fd381f7333d3acf709c81b1a2843d5ab16afd3707

Observation 50e3f239-8c77-4541-a534-c71bd44dec43 · outbound

This paper cites FedGraph: Federated Graph Learning with Intelligent Sampling.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks FedGraph: Federated Graph Learning with Intelligent Sampling

Reference 10

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local_arxiv, observed 2026-08-11T10:51:16.626942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.125178Z digest=sha256:a34aa62e1e5ab500670ae73e6aa2ee65bd67ee7eb0caac4068f75915686c01e3

Observation f6590624-0a01-4195-bfe7-c2f8edf0dbe2 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 11

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.129072Z digest=sha256:84497e9674ba3e995e97e35f4d4620c210d6bfb2c97c3db713b7452135eeb38f

Observation dccb0d63-9d5a-418f-a4d9-463b37d13724 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.132444Z digest=sha256:4373fb0b43f9cc694b0eff2d8a2959eca3404c6c387eeaf28d0be42b86faf1ca

Observation bc81ad5a-0916-460b-b6e7-f2461c131158 · outbound

This paper cites Adaptive Personalized Federated Learning.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Adaptive Personalized Federated Learning

Reference 13

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source=arxiv_source observed=2026-08-11T10:51:16.135599Z digest=sha256:7008e9bbc41dbc4a0ff20942ead20a43a89bebddf7d6ccedf7eeddd4eb7d246f

Observation 534a1f8b-84cc-4ae5-9247-85531171df6d · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.139355Z digest=sha256:e25ab72f08ef0defadd3d3d8f8f8886ddf1a16508a14ce05ba514c863e932e21

Observation e6ecfe14-7de9-4658-ba7d-9cd1e253b320 · outbound

This paper cites The proximal point method revisited.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks The proximal point method revisited

Reference 15

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source=arxiv_source observed=2026-08-11T10:51:16.142630Z digest=sha256:256f8dfd03bf05d9c348c824464e4118d440a3768505762713965076b37b333b

Observation c8e42de7-a507-4f1a-811d-b5ca9e72a814 · outbound

This paper cites Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization

Reference 16

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local_arxiv, observed 2026-08-11T10:51:16.595514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.146419Z digest=sha256:7663b73759acfd153bb70df1397b730ea0c6de995d7b47ffdada47c5a20a3f90

Observation 9ce3de62-1a44-4a4d-8e24-64c1c6864d08 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.150217Z digest=sha256:0e319081d67a82bd5f07d7283b3733a401ac9bac11072d650173452c150dd2c8

Observation 24dfa026-2f4d-4abc-b9a0-561c1c9acb1d · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.153434Z digest=sha256:4756dfe5cc83529e41d454de798f7cf3d1a10b82402de32297a2e9e1bbfb2f9e

Observation 37ee5286-528a-4350-b890-1318cfa97b87 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.156447Z digest=sha256:d557368da06aef73271c3b4a8837e95cf3881b7066f01d1be0e2efe4f3b5a953

Observation c198b6a3-f154-415c-a641-fd1c5b58332e · outbound

This paper cites Inductive Representation Learning on Large Graphs.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Inductive Representation Learning on Large Graphs

Reference 20

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source=arxiv_source observed=2026-08-11T10:51:16.159764Z digest=sha256:795160f50fc0c373a5b035b7de8684cebbdb5a310f4463436c7633ad8d6e06b9

Observation 8f9d2233-1f5a-4ee9-bfb2-aff60de1b4b9 · outbound

This paper cites FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks

Reference 21

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source=arxiv_source observed=2026-08-11T10:51:16.163144Z digest=sha256:8518a0b76ab1740b82c13958199fba7b401f3fea6cc611e309f43d9b84513273

Observation 10e24a96-6bcd-46b9-a6e3-b552f2f1dcf0 · outbound

This paper cites Deep Convolutional Networks on Graph-Structured Data.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Deep Convolutional Networks on Graph-Structured Data

Reference 22

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.166649Z digest=sha256:0275a1b1487521302583d59455b69a20f9b3321a68f5cfc1a5272b5e7aed9886

Observation c778a841-818f-42c2-af0c-3ad950b64bcc · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.170149Z digest=sha256:a63ec748170c1c3f136a18bd89c8d0cbb31f7ea25739886683a5b1844fcaa5ce

Observation 54d1a444-d423-457f-b371-049e6835f2a2 · outbound

This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 24

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.174153Z digest=sha256:7785b3ba2dd9a07fab64654a1cf6c9477739dea019e9e84fd4c9d266c16e659b

Observation c5b331e1-763f-4188-a5e3-c40e91ac76fc · outbound

This paper cites Open Graph Benchmark: Datasets for Machine Learning on Graphs.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 25

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no resolver link, observed 2026-08-11T10:51:16.178177Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.178177Z digest=sha256:9c35274f4de387fd7774a59333fe54621ccc3d3b2896504e5293ab8de1c8cb75

Observation 692c02c4-9083-411b-9529-61a4c7012b8b · outbound

This paper cites Heterogeneous Graph Transformer.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Heterogeneous Graph Transformer

Reference 26

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source=arxiv_source observed=2026-08-11T10:51:16.182047Z digest=sha256:8efa5c9209d08e05e5e5748bdef44de28029d59a144c5a39e0ccec66bdb0689a

Observation e363fc1e-5613-47a2-9464-b3b88e3ef715 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 27

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.185712Z digest=sha256:e5f14ff623f295158b9fbb676d08d8b75143cb3297fd1a2b33609cd6e50b6c8e

Observation b09481cc-9584-484a-8641-b050ecd2ac6b · outbound

This paper cites Adam: A Method for Stochastic Optimization.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Adam: A Method for Stochastic Optimization

Reference 28

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no resolver link, observed 2026-08-11T10:51:16.189645Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.189645Z digest=sha256:f941b7efb468d3ad1d21c8855d9f89337196eeb812c0f99edce63218cb83d63b

Observation fca85967-2c7a-488e-878c-ab88c0bb8d5b · outbound

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

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Semi-Supervised Classification with Graph Convolutional Networks

Reference 29

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.193640Z digest=sha256:32e21a3d391d25cd7a07282a2c57fc0386e05a05733ff4adaf42c044e45daccf

Observation caf19745-06fd-4c83-94e5-79bf5dcf49a7 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 30

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raw_fallback, observed 2026-08-11T10:51:16.809041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.197282Z digest=sha256:115c901f2b12fe5705e80b6bf8e1968492471b9f293ef17344fa79026b28772d

Observation 83709793-6896-4cff-9d3b-1d0a40a0e15c · outbound

This paper cites DeepGCNs: Can GCNs Go as Deep as CNNs?.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks DeepGCNs: Can GCNs Go as Deep as CNNs?

Reference 31

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.201976Z digest=sha256:a6f15555948a7c9f3a28ea0bd93ff5ce0d0890cb31541c2e63f9677bef17cb45

Observation 3db58ef4-92fc-4615-a229-763cb399a20d · outbound

This paper cites Federated Optimization in Heterogeneous Networks.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Federated Optimization in Heterogeneous Networks

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.205620Z digest=sha256:07d971014cfcc3ef7d49623ad4f9695afec1922cf7cb761b822e0ea0391d70a9

Observation 4f9ecb93-0763-400d-9fa8-45f0162568bd · outbound

This paper cites On the Convergence of FedAvg on Non-IID Data.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks On the Convergence of FedAvg on Non-IID Data

Reference 33

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no resolver link, observed 2026-08-11T10:51:16.209325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.209325Z digest=sha256:d943f10edd6fa8cd640a45dcadae4e5fa04c938ab461281fc15351f423fca6ec

Observation cf7266ce-93b8-46a2-a01b-0f6c6cfb52a9 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.213995Z digest=sha256:58d82ad116964b542deee11c90c98eef94690fedd17245da46b2626b0bcb7064

Observation 7aba0fdb-2bbb-464f-b7a7-740b38da8222 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.217550Z digest=sha256:0666659d3b034cb20275f720e786e4ad4e028b4e755a6135d87bb5f6779e4665

Observation 487d8355-6816-476b-85dc-7754b2c8314c · outbound

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

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 36

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.221033Z digest=sha256:b02948252ce402715b6facf3442651f9355c08a2b61a9b713b0984de25e7822a

Observation e8e1efab-faaa-4980-84df-1318a62b3b79 · outbound

This paper cites Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning

Reference 37

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verified exact
local_arxiv, observed 2026-08-11T10:51:16.472177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.224644Z digest=sha256:881fb8e4fdaa63e45413faa74541fae6d63cb7fb49f62a2affeba3508ad3541a

Observation 9643b646-3bce-41e6-9011-1b974fba1c61 · outbound

This paper cites Adaptive Federated Optimization.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Adaptive Federated Optimization

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T10:51:16.228634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.228634Z digest=sha256:aba34c67b92a5482a5c6483a85b358c4a0f50c9bb9dc98000b47c258a4b0bbfe

Observation c33b9803-d2ca-4c40-9853-1f562ce81cb5 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:51:16.782302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.232009Z digest=sha256:5d6909eeeeb6e7b6654cdf2b2855e79ebf206c19b94599dc7762d0fa775612d0

Observation 97492ef1-e858-4c25-aee4-b4d198669119 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:51:16.772807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.235732Z digest=sha256:5218ae1827d4ddcce229608ba90a6371c37e4f487653c6227e95141c9754f6da

Observation a326cdca-a004-46c2-ab14-f02b58e7de3e · outbound

This paper cites Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-11T10:51:16.446371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.239217Z digest=sha256:83ef7a553088fde0a2a80343bb7a44872cc1b11a846a7ec603ef452177c8882a

Observation 10d774cb-bfad-4ef2-9f21-cb3db37b640c · outbound

This paper cites Distributed Graph Neural Network Training: A Survey.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Distributed Graph Neural Network Training: A Survey

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-11T10:51:16.431941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.243995Z digest=sha256:90ea8bc7e6a08bd0e727dd8ed723b5c817f2425a6cf4fe53b2cb404b05500a10

Observation 730712b4-13ba-43da-81f8-cfde59ea3637 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:51:16.762903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.248062Z digest=sha256:0265de95b6c27143d62a464a540c3302f07b4bafe836be29176c5366ddbee704

Observation 87b18c05-1394-42ac-949b-50f933ace117 · outbound

This paper cites Towards Federated Graph Learning for Collaborative Financial Crimes Detection.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Towards Federated Graph Learning for Collaborative Financial Crimes Detection

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T10:51:16.251142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.251142Z digest=sha256:080b060e70c832038d4e034ea83439e13ba3771e63dd2ca9cba0b1b1583fcd14

Observation c863c40d-9f72-4042-a9a4-586b5d55917a · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:51:16.753164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.255409Z digest=sha256:d72b28ea03aab97214733d064b4fa17c94f82470ac86799b1de28ee857682069

Observation aa97125a-2403-4ab6-880e-8b7c332febef · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:51:16.743384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.259199Z digest=sha256:67f8745a6b59374b2cd54ceefa62b8f8adcd2ff70575c53d4c65e407e1fb1bda

Observation b1eb7866-dc4d-4620-9f0e-497edc63cad7 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:51:16.732922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.263326Z digest=sha256:6c15e2aea4014aa49b63e44135e44ed13af22ed5fe686732ec092834973ffc91

Observation cd93b770-0456-44b9-99fb-4b4eab48b623 · outbound

This paper cites N.; Kaiser, L.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks N.; Kaiser, L

Reference 48

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no resolver link, observed 2026-08-11T10:51:16.267165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.267165Z digest=sha256:271d40e33b4c61758a15887e2cc3cb2cb47ef2abbdbce73822bcfd3b4e16c406

Observation d92fa122-001b-406f-87c4-22c4952a574a · outbound

This paper cites Graph Attention Networks.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Graph Attention Networks

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-11T10:51:16.270466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.270466Z digest=sha256:3916343a77e6221427251068b62c1feef8d566b483bbe0cf1617f1f53f691706

Observation 9bd2c9f2-1963-414b-b1dc-b2ed57b5faba · outbound

This paper cites BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-11T10:51:16.274084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.274084Z digest=sha256:a00005ddc1aab6a41c8b61a3141ec903a6c8476c2755a8884cf1b8071d75b4a9

Observation 03601ffd-653a-4c6d-a051-bc92b3cd9213 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:51:16.717536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.277730Z digest=sha256:ba88478291b8dc4a90b748719df3bab2118f9c51754a5383a438dbe1819a4abf

Observation 687aa235-6aea-410c-9677-39daa0345800 · outbound

This paper cites FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks

Reference 52

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unresolved
no resolver link, observed 2026-08-11T10:51:16.281145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.281145Z digest=sha256:1eac1d962fd38f175d12573796bce468a8e6c2adcdb470940af762cd7b63509e

Observation 9606805b-7cec-4bb0-b651-a26969466014 · outbound

This paper cites M.; Cheng, Z.; Chen, L.; Joe-Wong, C.; and Liu, T.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks M.; Cheng, Z.; Chen, L.; Joe-Wong, C.; and Liu, T

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:51:16.706416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.284425Z digest=sha256:476dae749b38d2c0112478467ac7019da8f605fe6978988fc35c1689b6c049e2

Observation 535ea4b5-0f15-47b0-ae19-41c9b22b1567 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:51:16.696311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.287468Z digest=sha256:e57c0abd3ba3255caabba135d196771ff158daee09878c6e2c2283608a07e0ea

Observation 790c5921-8765-4564-ab48-edb77e265d36 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:51:16.686378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.291238Z digest=sha256:59f7e756d27606e567ac23c397262b9dc1e62ccd954961f3c52c7593c72288cb

Observation 2cf43f5d-5cca-4c80-b9e3-96e9097c32d0 · outbound

This paper cites Subgraph Federated Learning with Missing Neighbor Generation.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Subgraph Federated Learning with Missing Neighbor Generation

Reference 56

Resolution
verified exact
local_arxiv, observed 2026-08-11T10:51:16.375025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.294177Z digest=sha256:fc5598303f6b1c9be0a8370cebfe12e31afbf7207c534da6310d316f4bf1ca44

Observation 4c576e04-a07b-4825-ad3a-957a34d697e0 · outbound

This paper cites GMAN: A Graph Multi-Attention Network for Traffic Prediction.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks GMAN: A Graph Multi-Attention Network for Traffic Prediction

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-08-11T10:51:16.360752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.297807Z digest=sha256:99fc5a53600a6f81a65d48c2d7ab5f15dd95e65fbd9e4f0696db46cec07c24b0

Observation efa63a50-2f1e-4eb6-9656-d6e4e0fc7c4c · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 58

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:51:16.676320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.302129Z digest=sha256:ccdb6f48630efe242deb1ab32a8684b7212d0f8a7e8079ce62618b5f6a68456a

Observation c8974383-456d-411e-a242-a24e018b7236 · outbound

This paper cites an unresolved cited work.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-11T10:51:16.666162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.305614Z digest=sha256:c91f50eae82e1a93eb5fe9ef3e254ecd0cca0e9cc506895a4f6f6b8ad3f13d6d

Observation 634d7ade-7d8b-47cc-8f8f-3067bd22c701 · outbound

This paper cites ASFGNN: Automated Separated-Federated Graph Neural Network.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks ASFGNN: Automated Separated-Federated Graph Neural Network

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-08-11T10:51:16.345765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.308913Z digest=sha256:92735056fc8daccf4c46d4fb89790cebc92aba800b9fa7ce9afc15d2d1d2a65f

Pith citing papers

No inbound Pith citation observations are available.