Paper Citation Record · LEDGER

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection

As of 8 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2506.00654.

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

pith.paper-citation-record.v1
2506.00654 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:05:17.087915Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

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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

34 of 34 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e8c089d6-4d97-4f02-a326-b40f84bad797 · outbound

This paper cites Money laundering—a global obstacle,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Money laundering—a global obstacle,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:20.626194Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9efcd4ce-237b-4cd4-b8d0-8d936548513d · outbound

This paper cites Payments statistics: 2020,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Payments statistics: 2020,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:20.522857Z

Source-reported events for the cited work

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Observation ac111c48-5522-413d-941b-ddc6b24533f3 · outbound

This paper cites Application of data mining for anti- money laundering detection: A case study,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Application of data mining for anti- money laundering detection: A case study,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:20.382020Z

Source-reported events for the cited work

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Observation da449d9c-e396-46c0-b4e0-a7ac8f9f4d3b · outbound

This paper cites Fraud detection decision support system for indonesian financial institution,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Fraud detection decision support system for indonesian financial institution,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:20.253306Z

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Observation f09a3745-63b6-44a2-b12d-4132ec0f6ada · outbound

This paper cites A new algorithm for money laundering detection based on structural similarity,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection A new algorithm for money laundering detection based on structural similarity,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:20.132513Z

Source-reported events for the cited work

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Observation 56017539-81dd-47e6-8258-03fe0210a2c1 · outbound

This paper cites Detecting money laundering using filtering techniques: a multiple-criteria index,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Detecting money laundering using filtering techniques: a multiple-criteria index,

Reference 6

Resolution: verified exact; doi, observed 2026-08-07T12:05:17.615545Z

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Observation 4a1909a3-ec06-4e73-96ae-4ca38d4673a3 · outbound

This paper cites Deep learning anomaly detection as support fraud investigation in brazilian exports and anti-money laundering,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Deep learning anomaly detection as support fraud investigation in brazilian exports and anti-money laundering,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:19.993268Z

Source-reported events for the cited work

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Observation 2d7e55c5-ff14-4e85-8e82-55daf52a2962 · outbound

This paper cites Analyzing and detecting money-laundering accounts in online social networks,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Analyzing and detecting money-laundering accounts in online social networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:19.932216Z

Source-reported events for the cited work

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Observation 041442d6-df21-469c-bbf8-3c3c1e9a0df8 · outbound

This paper cites Machine learning and sampling scheme: An empirical study of money laundering detection,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Machine learning and sampling scheme: An empirical study of money laundering detection,

Reference 9

Resolution: verified exact; doi, observed 2026-08-07T12:05:17.502828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5b0f735d-5ef8-492f-8bab-9b3fb1651b93 · outbound

This paper cites Detecting money laundering transactions with machine learning,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Detecting money laundering transactions with machine learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:19.821468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6d085ee0-406a-4a5a-b380-96bfff049a67 · outbound

This paper cites Intelligent anti-money laundering solution based upon novel community detection in massive transaction networks on spark,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Intelligent anti-money laundering solution based upon novel community detection in massive transaction networks on spark,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:19.693332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 959d9d8e-0fe6-47d3-bac0-7e30a561c6cf · outbound

This paper cites Autoregressive-based outlier algorithm to detect money laundering activities,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Autoregressive-based outlier algorithm to detect money laundering activities,

Reference 12

Resolution: verified exact; doi, observed 2026-08-07T12:05:17.230593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 38585f3a-22cb-49ca-a954-3985e3db654d · outbound

This paper cites Amaretto: An active learning framework for money laundering detection,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Amaretto: An active learning framework for money laundering detection,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:19.586543Z

Source-reported events for the cited work

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Observation 1f12077e-8758-4009-8750-921ad04544ba · outbound

This paper cites Detection of money laundering groups using supervised learning in networks,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Detection of money laundering groups using supervised learning in networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:19.423740Z

Source-reported events for the cited work

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Observation 44b7fc03-6341-4d8d-bedc-982e93283b97 · outbound

This paper cites A study on gcn using focal loss on class- imbalanced bitcoin transaction for anti-money laundering detection,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection A study on gcn using focal loss on class- imbalanced bitcoin transaction for anti-money laundering detection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:19.306343Z

Source-reported events for the cited work

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Observation 280d3b3c-7f98-4bd7-898d-b5e07fc30f4c · outbound

This paper cites Semi-supervised classification with graph convolutional networks,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Semi-supervised classification with graph convolutional networks,

Reference 16

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Source-reported events for the cited work

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Observation 2e0a73eb-0761-4799-9519-e2f1d9101045 · outbound

This paper cites Anti-money laundering in bitcoin: Experimenting with graph convolutional networks for financial foren- sics,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Anti-money laundering in bitcoin: Experimenting with graph convolutional networks for financial foren- sics,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:19.184784Z

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Observation 27d9f277-84bb-469b-a7d5-606cc5c36d70 · outbound

This paper cites Catch me if you can: Semi-supervised graph learning for spotting money laundering,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Catch me if you can: Semi-supervised graph learning for spotting money laundering,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:19.034910Z

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Observation 9a547d2b-38f4-454c-8af6-03d00d61e7d8 · outbound

This paper cites Laundrograph: Self-supervised graph representation learning for anti-money laundering,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Laundrograph: Self-supervised graph representation learning for anti-money laundering,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:18.923626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 695956eb-5c13-46a8-a3cf-f96256729e29 · outbound

This paper cites Inductive representation learning on large graphs,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Inductive representation learning on large graphs,

Reference 20

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Source-reported events for the cited work

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Observation 52f793f5-33b4-4303-82a5-7b02c76363c8 · outbound

This paper cites Evolvegcn: Evolving graph convolutional networks for dynamic graphs,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Evolvegcn: Evolving graph convolutional networks for dynamic graphs,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:18.782792Z

Source-reported events for the cited work

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Observation a1671004-7a8d-4337-8871-9ae6763abd88 · outbound

This paper cites Long short-term memory,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Long short-term memory,

Reference 22

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Observation 391d41c8-f418-4a2a-b7a9-b0cf15418707 · outbound

This paper cites Graph neural networks: A review of methods and applications,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Graph neural networks: A review of methods and applications,

Reference 23

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Source-reported events for the cited work

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Observation 8f9fd822-69a6-4d8d-8efb-cec0cfc6a538 · outbound

This paper cites Graph convolutional networks: a comprehensive review,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Graph convolutional networks: a comprehensive review,

Reference 24

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Source-reported events for the cited work

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Observation b1c1e915-24ec-4a2e-be9d-03019caf68d5 · outbound

This paper cites Graph Attention Networks.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Graph Attention Networks

Reference 25

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Observation e6b7b4f7-f202-4a5f-9759-4af905b1d004 · outbound

This paper cites Scalable graph learning for anti-money laundering: A first look,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Scalable graph learning for anti-money laundering: A first look,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:18.677559Z

Source-reported events for the cited work

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Observation 49f7ac50-4ef0-4ac7-a83b-2a176587e31a · outbound

This paper cites The anatomy of a large-scale hypertextual web search engine,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection The anatomy of a large-scale hypertextual web search engine,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:18.553727Z

Source-reported events for the cited work

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Observation c185e0ca-5688-477b-86fb-974f9f61dfd2 · outbound

This paper cites Optimization of graph neural networks: Implicit acceleration by skip connections and more depth,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Optimization of graph neural networks: Implicit acceleration by skip connections and more depth,

Reference 28

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Observation 80625479-1520-41ee-9b67-941d4c1eb2c7 · outbound

This paper cites It-aml dataset, kaggle url,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection It-aml dataset, kaggle url,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:18.274520Z

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Observation 4bc8c6a9-fcbe-4db0-8376-3b3f50a817ab · outbound

This paper cites Realistic synthetic financial transactions for anti-money laundering models,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Realistic synthetic financial transactions for anti-money laundering models,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:18.151564Z

Source-reported events for the cited work

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Observation ee92a875-914e-47cc-8fb9-eb12ad624746 · outbound

This paper cites Anti-Money Laundering Datasets: InPlusLab anti-money laundering datadatasets,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Anti-Money Laundering Datasets: InPlusLab anti-money laundering datadatasets,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:17.991962Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1fd6757e-660a-426c-bc1e-58b02d4054ab · outbound

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Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:05:17.872320Z

Source-reported events for the cited work

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Observation 069693f4-a909-411c-b6a4-ae96779ece1c · outbound

This paper cites A study of cross-validation and bootstrap for accuracy estimation and model selection,.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection A study of cross-validation and bootstrap for accuracy estimation and model selection,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:17.735068Z

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Observation 36989d5d-156c-4424-8ae4-44e716022c15 · outbound

This paper cites Available: https://doi.org/10.1108/JMLC-07-2019-0055.

Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection Available: https://doi.org/10.1108/JMLC-07-2019-0055

Reference 2020

Resolution: verified exact; doi, observed 2026-08-07T12:05:17.342404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.