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Paper Citation Record · LEDGER

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

As of 15 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 2026-08-15T06:32:42.880941+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:bc1096c363de30e3fe437429cccef0f040e28b9d4cc0a7cc59ec32a00915bb3b

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:a0f7f1e59bc3bc8188e5fd244f6c3d408a5cb1a042311ded55b98bfb80af1e0b

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.098984Z digest=sha256:5d60ec18e965d7ded1343267c4c0affa2fcc67b201b2bca5d7d785bc6cb0193e

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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verified fuzzy
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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.102412Z digest=sha256:05b68886b3e2b2477ebd17d6f8e4aac0feacd06f91941274d62072338d2f1b5e

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.105884Z digest=sha256:32f66ac196f3213faa6ed15ac30d44791374f28470541f6de983add8978f39d7

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=sha256:1af857200357cf43fd6d2a9415af47b6fb7ae5a3bd4b6407c4b3335f3578985c

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=sha256:2b69516edb13f1aa2608bd9550847894b4ab46d2998b407be1ad3ba9e76b7529

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.117584Z digest=sha256:ab2b8965781fe857d5cd4be7afe0ad17c8fa35051cf552aafaf45a5708af8296

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:c57563280b1c9d9bbfe852b050d248c05f59613a5e872d5009345062e2b9da43

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.125178Z digest=sha256:5d75203552a1326cf1177a59e8c2fbe5e4ee0230f432462edc9b68829323a46f

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.129072Z digest=sha256:d765caa24490f77c0077b8d58b5aebff0f2bdcc95f74e782b1f296e24165a5a4

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.132444Z digest=sha256:96090b1103ba223492c1812b57b809c7fec478f28cfd3398090106eed8938312

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:d579b0c0d9b3370266b63a87e493f76180a65fb3b1b7bd9e05f785e80066bf76

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.139355Z digest=sha256:496f6b1708f05cce8261e285c5a050b8465140188af0e93ad14a1f85f712eaf9

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.142630Z digest=sha256:5476ea60caa92bbc016709fc2caa17a023e78caaccaaf6704881cbbeb1f1c4ad

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.146419Z digest=sha256:1df5e526785a325e4f7bff881aa5e1cbbff2e76cd2705e3b744e5baf0dfcf27f

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.150217Z digest=sha256:a8f6906ec8efe1e83856322916a2b589f10ca768e4605a32f10d98cc1173dd29

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.153434Z digest=sha256:a7f8b6a4600ecc77b9d637137cccad2509ce7e515d5d4c468e88913844254ffe

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.156447Z digest=sha256:67ed4183ea8d2eed7e99d7daa05a92ee9bad7cc5658073421d37f27b06c4d1b6

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=sha256:16b2c408932b336a41af090435cd1f5606f5139ec82a332ba8aa5aaf414e8b28

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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no resolver link, observed 2026-08-11T10:51:16.163144Z

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source=arxiv_source observed=2026-08-11T10:51:16.163144Z digest=sha256:c003600df32ae665b765784e777599b56b2a25f7daa4853d32ea3b51929ccdf9

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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source=arxiv_source observed=2026-08-11T10:51:16.166649Z digest=sha256:281824be5f78ea0431d8bd4915a9b6072acf06bafb705d2024f92baa96589b39

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.170149Z digest=sha256:8ea45d419cbb84c555c7d7fea706fb1f778a54dfa096f3afd1aa6c6b520f7532

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=sha256:8928e3f3d852cc07690bd22ccdd09ac99593596a5dee475ba026e39036e791b5

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:ad73bfe92df3634c41a97389221459413836da31824642f7ca61d3c8be1c7274

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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no resolver link, observed 2026-08-11T10:51:16.182047Z

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source=arxiv_source observed=2026-08-11T10:51:16.182047Z digest=sha256:3d8ed262a6362f6f40bc818bc63361587a2a3bf44796821496fa02b08ab349dd

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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raw_fallback, observed 2026-08-11T10:51:16.819290Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.185712Z digest=sha256:85ddc1245bb753715ff095ed88a814e6f23b15c810ec1e08032d692a9e91f6cc

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=sha256:1f6fcdde8fabc896a618ba309fddafd8c44a6125617ba6b3e4e4cf4e9ae91251

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=sha256:5a727a9c9b3eb5311b1954a957c84c11d5970b1cffbf54288a0be3db81d16361

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.197282Z digest=sha256:c27b5a6a87381423d01f9c298f829221e8c5dd5b5fc54a5195b6ebf56a7ac4fb

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:51:16.201976Z digest=sha256:907f964ae4ba6518c986891d956e78c079aef3d7f51303d1af6ac0863556b368

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=sha256:7a66a363935ecbf4012186f3e55a9d5aa062f9e47052134469e854f7802df835

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=sha256:43744b81f9e223923621d46566a1d4557e38d86cdeb948a8fb61ddbf8d0cfe8e

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.213995Z digest=sha256:1b3d6d4e4fd00d35456b4ac1d1cc15ff76ea04c784922d62c426e757c2132b57

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:ee90851bdef9190bea6d3c7c46a6d2290871834d4d5d9f1de5324b988b9b0934

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=sha256:4e77b6df84651cb1233af227dc6b580d7ad4540f9a1c9cbaf7fa4db27a4ec5c2

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.224644Z digest=sha256:1a7a368662500175bc1bdc9df5ff9eabd2eef823c3f9604f5ea2258a395a1291

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=sha256:6e3c0001176bbbe35427a0c29b1da50b4ab7a3b54edda7ca70ee09a2fbfb3487

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.232009Z digest=sha256:d8a136b2364a396c9bfa50103eb0c1b34c637b495803dad52f3dcecaebef61eb

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.235732Z digest=sha256:9f0cab01d2b87c288dcbe42b2854519fe93c06d8dc60ac65060706ef4e1f138d

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.239217Z digest=sha256:52738ef712064e8507c82f9137b62d8d1cee0cc5c2c14af2324aa8b44cc0b264

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.243995Z digest=sha256:6d563b2a13d42af770c056f8b380a0a0c31fbb85600a93b0e3cc09f77058c0de

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.248062Z digest=sha256:649e36835fd3424e6012825a5feebdd2e173d4325089ebe204e369c05ab560d6

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:d40c65043a10d74a9e24e8354d72162efb5650fad411f69d6f06d5eb3e856382

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.255409Z digest=sha256:b0fbcd83030e173a60fd48c261eae9c21b0e19e75e7649360e78ede59eb26555

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.259199Z digest=sha256:b11ca1a6169f89fe576ea604058239986b3ffab2fe9d0da17968c50646e8b429

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.263326Z digest=sha256:ac2414fc3e2810bb70951e7dff1d93b1748438edd8b747837cacbfd301f28d89

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

Resolution
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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=sha256:0bed7272d1e9089860bd2afa8b729edbe1e8b2f1b647b1665582d0ceba5e6a49

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=sha256:048ee4e472edef58c27fd9ede9c1fff99242db40e9402459d13a2178961abe93

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=sha256:75d6c59eec84812c9fdb5c71315cb14c95bf5930bf69e21e022bb605de1ab78b

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.277730Z digest=sha256:74737b66a3f75f42d9de55a9f13ece5330b267eda82f49ebfdadc6f4da97e606

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

Resolution
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:ef59857cb2457d12f6784d8a17ddce2d016477a2b9b343ad03b5aac4ea4920e6

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.284425Z digest=sha256:f1c9b1dfa1c1d36a687bacad7b86dab78b382f6124c03c07ed1f797613cf6c8d

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.287468Z digest=sha256:c9ccc2ba8b37a6dcba2a81d3a5e0748967777da7291cba041c5a38d8cc60ab0f

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.291238Z digest=sha256:6ae6415e9e035c8b6d303ab99b96004fb8bc085e5b9e19451b1d14bc0e8a0c9a

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.294177Z digest=sha256:fe3c607babc5eb7deba0526f7779561688a9a2894a0122a8114c748a19910884

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.297807Z digest=sha256:ebc52bcf4be155179761985554cb7dcf74aa71a8c5a165a7070f6c42ab6f5fee

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.302129Z digest=sha256:01d88b03f9fa1fa23962754b609c7a70e4d81654888182462a81cb45ec01e456

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.305614Z digest=sha256:e1abb8bac4c98db214696a7dff6052bf5c87b13a75d66dd4cfe3adbec2d5c171

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T10:51:16.308913Z digest=sha256:bb07a184b6b7e757927237d3ede84bc55f9d4e0c08005537f150f7c4c18ed8bd

Pith citing papers

No inbound Pith citation observations are available.